MIFT Study 2 Analyses
About the study
From preregistration:
Hypothesis: Participants who believe that multiracial identity is MORE FLUID will be more likely to show LOWER TRUST for multiracial people, more NEGATIVE ATTITUDES toward multiracial people, and will perceive multiracial people as LESS AUTHENTIC.*
Dependent Variables: 1) Perceptions of Multiracial Identity Fluidity a) Perceptions of Multiracial Identity Fluidity Scale
- Trust
- Speeded Trust Task
- Trust Thermometers
- Trust Survey
- Explicit Attitudes
- Feeling Thermometers
- Attitudes Toward Multiracial Adults Scale
- Authenticity
- Authenticity Scale
Conditions: As this is a correlational study, participants will not be assigned to conditions. All participants will receive the same measures.
Findings: - fluidity – mean is not particularly low or high (no floor vs ceiling effect)
Descriptive Statistics
vars | n | mean | sd | median | trimmed | |
---|---|---|---|---|---|---|
whitemulti_trust_dif | 1 | 297 | 0.02683 | 0.3997 | 0.025 | 0.03621 |
White | 2 | 297 | 2.887 | 0.5357 | 2.9 | 2.873 |
Multiracial | 3 | 297 | 2.86 | 0.4899 | 2.85 | 2.846 |
Black | 4 | 297 | 3.089 | 0.5556 | 3.1 | 3.094 |
trust_survey | 5 | 296 | 4.838 | 0.8399 | 4.8 | 4.776 |
fluidity | 6 | 296 | 4.45 | 0.8086 | 4.571 | 4.475 |
fluidity_should | 7 | 296 | 4.439 | 1.129 | 4.429 | 4.456 |
biracial_pref | 8 | 297 | 3.82 | 1.032 | 4 | 3.872 |
biracial_loyalty | 9 | 297 | 3.233 | 0.9798 | 3.25 | 3.272 |
biracial_cat | 10 | 297 | 3.632 | 0.7259 | 4 | 3.755 |
trust_therm_multiracial | 11 | 296 | 67.69 | 18.56 | 69.5 | 67 |
trust_therm_black | 12 | 296 | 65.74 | 20.28 | 65 | 65.53 |
trust_therm_white | 13 | 296 | 62.95 | 20.93 | 60 | 63.14 |
atma | 14 | 296 | 3.421 | 0.353 | 3.391 | 3.412 |
feel_therm_multiracial | 15 | 296 | 69.65 | 18.26 | 70 | 69.11 |
feel_therm_black | 16 | 296 | 67.83 | 20.87 | 70 | 68.16 |
feel_therm_white | 17 | 295 | 62.58 | 20.58 | 61 | 62.69 |
authen | 18 | 296 | 5.079 | 0.9453 | 5 | 5.067 |
race_ess | 19 | 296 | 4.252 | 0.9195 | 4.25 | 4.273 |
pol_or | 20 | 297 | 2.97 | 1.266 | 3 | 2.933 |
mad | min | max | range | skew | |
---|---|---|---|---|---|
whitemulti_trust_dif | 0.3706 | -1.95 | 1.025 | 2.975 | -0.4947 |
White | 0.4448 | 1.35 | 5 | 3.65 | 0.3768 |
Multiracial | 0.4077 | 1.625 | 4.85 | 3.225 | 0.5418 |
Black | 0.4818 | 1.525 | 4.95 | 3.425 | 0.007934 |
trust_survey | 1.186 | 3.2 | 6.8 | 3.6 | 0.4152 |
fluidity | 0.8472 | 2 | 6.286 | 4.286 | -0.3154 |
fluidity_should | 1.059 | 1 | 7 | 6 | -0.1442 |
biracial_pref | 0.7413 | 1 | 7 | 6 | -0.4586 |
biracial_loyalty | 1.112 | 1 | 6.75 | 5.75 | -0.2612 |
biracial_cat | 0 | 1 | 5.333 | 4.333 | -1.439 |
trust_therm_multiracial | 25.2 | 17 | 100 | 83 | 0.1298 |
trust_therm_black | 22.24 | 4 | 100 | 96 | 0.03856 |
trust_therm_white | 19.27 | 1 | 100 | 99 | -0.1126 |
atma | 0.3868 | 2.435 | 4.435 | 2 | 0.1954 |
feel_therm_multiracial | 25.2 | 22 | 100 | 78 | 0.09672 |
feel_therm_black | 29.65 | 8 | 100 | 92 | -0.1018 |
feel_therm_white | 19.27 | 1 | 100 | 99 | -0.06849 |
authen | 1.112 | 3 | 7 | 4 | 0.03273 |
race_ess | 0.9266 | 1.5 | 6.625 | 5.125 | -0.2121 |
pol_or | 1.483 | 1 | 7 | 6 | 0.2456 |
kurtosis | se | |
---|---|---|
whitemulti_trust_dif | 1.799 | 0.02319 |
White | 0.9204 | 0.03108 |
Multiracial | 1.539 | 0.02842 |
Black | 0.5024 | 0.03224 |
trust_survey | -0.8702 | 0.04882 |
fluidity | -0.1375 | 0.047 |
fluidity_should | -0.06536 | 0.06562 |
biracial_pref | 0.675 | 0.05987 |
biracial_loyalty | 0.2085 | 0.05685 |
biracial_cat | 2.583 | 0.04212 |
trust_therm_multiracial | -0.7929 | 1.079 |
trust_therm_black | -0.6744 | 1.179 |
trust_therm_white | -0.3048 | 1.217 |
atma | -0.07175 | 0.02052 |
feel_therm_multiracial | -0.9452 | 1.062 |
feel_therm_black | -0.7131 | 1.213 |
feel_therm_white | -0.3484 | 1.198 |
authen | -0.6494 | 0.05495 |
race_ess | 0.06929 | 0.05344 |
pol_or | -0.6774 | 0.07348 |
GEE Model for Speeded Trust Task
From preregistration:
For the speeded trust task, we will fit a GEE regression model with trustworthiness ratings for each target face as the outcome and target race (within subjects—will be dummy coded with White as the comparison group), perceptions of multiracial identity fluidity, and their interactions as predictors.
Findings:
xxx
## (Intercept) fluidity race_multi race_black
## 2.9767634 -0.0217154 -0.1126866 -0.0782192
## fluidity:race_multi fluidity:race_black
## 0.0183493 0.0621544
term | estimate | std.error | statistic | p.value | NA |
---|---|---|---|---|---|
(Intercept) | 2.9768 | 0.0552 | 53.9628 | 0.1796 | 16.5766 |
fluidity | -0.0217 | 0.0122 | -1.7755 | 0.0398 | -0.5461 |
race_multi | -0.1127 | 0.0781 | -1.4428 | 0.1364 | -0.8260 |
race_black | -0.0782 | 0.0781 | -1.0011 | 0.2036 | -0.3841 |
fluidity:race_multi | 0.0183 | 0.0173 | 1.0597 | 0.0311 | 0.5897 |
fluidity:race_black | 0.0622 | 0.0173 | 3.5882 | 0.0458 | 1.3567 |
## Estimate Naive S.E. Naive z Robust S.E. Robust z
## (Intercept) 2.9767634 0.0551632 53.96281 0.1795766 16.576571
## fluidity -0.0217154 0.0122307 -1.77548 0.0397636 -0.546113
## race_multi -0.1126866 0.0781006 -1.44284 0.1364256 -0.825993
## race_black -0.0782192 0.0781350 -1.00108 0.2036202 -0.384142
## fluidity:race_multi 0.0183493 0.0173150 1.05974 0.0311137 0.589749
## fluidity:race_black 0.0621544 0.0173220 3.58818 0.0458117 1.356736
## (Intercept)
## 0.000000000000000000000000000000000000000000000000000000000000102937
## fluidity
## 0.584988465714838312692336330655962228775024414062500000000000000000
## race_multi
## 0.408807883679895900375100836754427291452884674072265625000000000000
## race_black
## 0.700872839963326943468757690425263717770576477050781250000000000000
## fluidity:race_multi
## 0.555358802672816009859957375738304108381271362304687500000000000000
## fluidity:race_black
## 0.174865195836332004697410980043059680610895156860351562500000000000
Pearson correlation for trust, feeling therm, atma, and authenticty
From preregistration:
For each of the five other main variables of interest (listed below), we will run Pearson correlations to determine if there is any relation between participants perception of multiracial identity fluidity and each of the variables. Due to the large number of analyses, we will use a Bonferroni correction to correct for multiple comparisons, using an alpha level of .01 (.05 / 5 = .01) for each correlation.
## [1] "race_ess" "fluidity"
## [3] "trust_therm_multiracial" "trust_therm_black"
## [5] "trust_therm_white" "trust_survey"
## [7] "feel_therm_multiracial" "feel_therm_black"
## [9] "feel_therm_white" "atma"
## [11] "authen" "whitemulti_trust_dif"
## [13] "White" "Multiracial"
## [15] "Black"
##
## CORRELATION MATRIX
##
## Correlation Matrix
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## race_ess fluidity trust_therm_multiracial trust_therm_black trust_therm_white trust_survey feel_therm_multiracial feel_therm_black feel_therm_white atma authen whitemulti_trust_dif White Multiracial Black
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## race_ess Pearson's r —
## df —
## p-value —
##
## fluidity Pearson's r -0.141549 —
## df 294 —
## p-value 0.014798 —
##
## trust_therm_multiracial Pearson's r -0.064788 0.042833 —
## df 294 294 —
## p-value 0.266521 0.462857 —
##
## trust_therm_black Pearson's r -0.104555 0.075492 0.878947 —
## df 294 294 294 —
## p-value 0.072472 0.195265 < .000001 —
##
## trust_therm_white Pearson's r 0.016738 -0.042598 0.657025 0.505089 —
## df 294 294 294 294 —
## p-value 0.774289 0.465320 < .000001 < .000001 —
##
## trust_survey Pearson's r -0.055668 0.070039 0.445001 0.438507 0.233582 —
## df 294 294 294 294 294 —
## p-value 0.339861 0.229608 < .000001 < .000001 0.000050 —
##
## feel_therm_multiracial Pearson's r -0.053409 0.111470 0.630687 0.613993 0.343857 0.405752 —
## df 294 294 294 294 294 294 —
## p-value 0.359850 0.055408 < .000001 < .000001 < .000001 < .000001 —
##
## feel_therm_black Pearson's r -0.072851 0.089622 0.618631 0.710976 0.286200 0.376972 0.847407 —
## df 294 294 294 294 294 294 294 —
## p-value 0.211398 0.123931 < .000001 < .000001 < .000001 < .000001 < .000001 —
##
## feel_therm_white Pearson's r 0.059384 0.033733 0.452510 0.339852 0.639132 0.251609 0.560170 0.441987 —
## df 293 293 293 293 293 293 293 293 —
## p-value 0.309382 0.563883 < .000001 < .000001 < .000001 0.000012 < .000001 < .000001 —
##
## atma Pearson's r -0.040402 -0.227287 0.122677 0.135770 0.124292 0.273195 0.168283 0.185392 0.187265 —
## df 294 294 294 294 294 294 294 294 293 —
## p-value 0.488661 0.000080 0.034887 0.019448 0.032545 0.000002 0.003687 0.001356 0.001232 —
##
## authen Pearson's r -0.090582 0.017267 0.355394 0.326596 0.273675 0.417898 0.273836 0.240773 0.292888 0.387133 —
## df 294 294 294 294 294 294 294 294 293 294 —
## p-value 0.119937 0.767350 < .000001 < .000001 0.000002 < .000001 0.000002 0.000028 < .000001 < .000001 —
##
## whitemulti_trust_dif Pearson's r 0.010527 -0.028164 -0.142378 -0.230193 0.191497 -0.187208 -0.214286 -0.253019 0.114861 0.039684 -0.057161 —
## df 294 294 294 294 294 294 294 294 293 294 294 —
## p-value 0.856877 0.629381 0.014218 0.000064 0.000928 0.001213 0.000204 0.000011 0.048729 0.496421 0.327046 —
##
## White Pearson's r -0.072493 -0.039209 0.158602 0.068181 0.353758 0.010237 -0.044260 -0.082720 0.227702 0.100937 0.171766 0.482815 —
## df 294 294 294 294 294 294 294 294 293 294 294 295 —
## p-value 0.213653 0.501592 0.006248 0.242231 < .000001 0.860780 0.448077 0.155727 0.000079 0.082977 0.003029 < .000001 —
##
## Multiracial Pearson's r -0.088332 -0.019612 0.292529 0.266323 0.229023 0.166962 0.129666 0.119668 0.154471 0.077786 0.236094 -0.287890 0.699650 —
## df 294 294 294 294 294 294 294 294 293 294 294 295 295 —
## p-value 0.129457 0.736857 < .000001 0.000003 0.000070 0.003969 0.025691 0.039635 0.007865 0.181991 0.000041 < .000001 < .000001 —
##
## Black Pearson's r -0.143572 0.045859 0.325780 0.383333 0.061726 0.253491 0.225099 0.287060 0.037957 0.169317 0.304808 -0.324099 0.387644 0.688342 —
## df 294 294 294 294 294 294 294 294 293 294 294 295 295 295 —
## p-value 0.013418 0.431834 < .000001 < .000001 0.289829 0.000010 0.000094 < .000001 0.516077 0.003480 < .000001 < .000001 < .000001 < .000001 —
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
##
## CORRELATION MATRIX
##
## Correlation Matrix
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## fluidity fluidity_should whitemulti_trust_dif White Multiracial Black biracial_pref biracial_cat biracial_loyalty race_ess
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## fluidity Pearson's r —
## df —
## p-value —
##
## fluidity_should Pearson's r 0.511646 —
## df 294 —
## p-value < .000001 —
##
## whitemulti_trust_dif Pearson's r -0.028164 -0.078632 —
## df 294 294 —
## p-value 0.629381 0.177274 —
##
## White Pearson's r -0.039209 0.032253 0.482815 —
## df 294 294 295 —
## p-value 0.501592 0.580470 < .000001 —
##
## Multiracial Pearson's r -0.019612 0.100812 -0.287890 0.699650 —
## df 294 294 295 295 —
## p-value 0.736857 0.083361 < .000001 < .000001 —
##
## Black Pearson's r 0.045859 0.164168 -0.324099 0.387644 0.688342 —
## df 294 294 295 295 295 —
## p-value 0.431834 0.004629 < .000001 < .000001 < .000001 —
##
## biracial_pref Pearson's r -0.043199 -0.066002 0.103974 0.081173 0.003938 -0.084407 —
## df 294 294 295 295 295 295 —
## p-value 0.459044 0.257649 0.073591 0.162920 0.946116 0.146750 —
##
## biracial_cat Pearson's r -0.015173 0.037451 0.049927 0.087305 0.054739 -0.019915 0.352458 —
## df 294 294 295 295 295 295 295 —
## p-value 0.794897 0.520983 0.391257 0.133327 0.347173 0.732499 < .000001 —
##
## biracial_loyalty Pearson's r -0.087895 -0.105795 0.057561 0.122138 0.086603 -0.046751 0.470273 0.349482 —
## df 294 294 295 295 295 295 295 295 —
## p-value 0.131370 0.069129 0.322843 0.035388 0.136491 0.422128 < .000001 < .000001 —
##
## race_ess Pearson's r -0.141549 -0.247437 0.010527 -0.072493 -0.088332 -0.143572 0.128521 0.028623 0.008379 —
## df 294 294 294 294 294 294 294 294 294 —
## p-value 0.014798 0.000017 0.856877 0.213653 0.129457 0.013418 0.027037 0.623799 0.885849 —
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Exploratory Analyses.
Fluidity and essentialism
From preregistration: ” We will run exploratory analyses to examine whether race essentialism moderates the relationship between perceptions of multiracial identity fluidity and each of the six main variables of interest.”
Speeded trust task with White/Multiracial trust diff score as outcome + fluidity, race essentialism, and interaction as predictors
From preregistration:
“For the speeded trust task, we will first calculate a White/Multiracial trust difference score by subtracting participant’s average trust ratings for all multiracial targets from participant’s average trust ratings for all White targets, with a higher number indicating greater trust towards White targets relative to multiracial targets.
We then will fit a linear regression model with the White/Multiracial trust difference score as the outcome and perceptions of multiracial identity fluidity, race essentialism, and the interaction term between the two as predictors. If we find that the interaction is significant, we will conduct simple slopes analysis to probe the interaction.
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | -0.4065 | 0.6389 | -0.6362 | 0.5251 |
race_ess | 0.1107 | 0.1396 | 0.7932 | 0.4283 |
fluidity | 0.0917 | 0.1370 | 0.6694 | 0.5038 |
race_ess:fluidity | -0.0237 | 0.0301 | -0.7858 | 0.4326 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0029 | -0.0073 | 0.4018 | 0.2875 | 0.8344 | 3 | -148.1 | 306.199 | 324.651 | 47.1416 | 292 | 296 |
Other main DVs as outcomes with fluidity, race essentialism, and interaction as predictors
From preregistration:
For each of the five other dependent variables, we will fit an individual linear regression model including perceptions of multiracial identity fluidity, race essentialism, and the interaction term between the two as predictors. If we find a significant interaction between perceptions of multiracial identity fluidity and race essentialism for any of the models, we will conduct simple slopes analysis for that model to probe the interaction.”
Trust survey
Findings:
Main Effects
Interaction
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 5.0333 | 1.3373 | 3.7636 | 0.0002 |
race_ess | -0.1114 | 0.2922 | -0.3814 | 0.7032 |
fluidity | -0.0012 | 0.2869 | -0.0044 | 0.9965 |
race_ess:fluidity | 0.0151 | 0.0631 | 0.2395 | 0.8109 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0072 | -0.003 | 0.8411 | 0.7095 | 0.547 | 3 | -366.769 | 743.538 | 761.99 | 206.573 | 292 | 296 |
Trust Thermometer
Findings:
Main Effects
Interaction
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 73.6595 | 29.5859 | 2.4897 | 0.0133 |
race_ess | -2.1815 | 6.4639 | -0.3375 | 0.7360 |
fluidity | -0.1596 | 6.3460 | -0.0252 | 0.9799 |
race_ess:fluidity | 0.2134 | 1.3954 | 0.1529 | 0.8786 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0054 | -0.0048 | 18.6074 | 0.5318 | 0.6608 | 3 | -1283.37 | 2576.73 | 2595.18 | 101101 | 292 | 296 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 65.0107 | 32.1699 | 2.0209 | 0.0442 |
race_ess | -1.4844 | 7.0284 | -0.2112 | 0.8329 |
fluidity | 2.1663 | 6.9003 | 0.3139 | 0.7538 |
race_ess:fluidity | -0.1380 | 1.5172 | -0.0909 | 0.9276 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0147 | 0.0046 | 20.2326 | 1.454 | 0.2273 | 3 | -1308.15 | 2626.3 | 2644.76 | 119533 | 292 | 296 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 49.9893 | 33.4022 | 1.4966 | 0.1356 |
race_ess | 3.9759 | 7.2977 | 0.5448 | 0.5863 |
fluidity | 2.5747 | 7.1646 | 0.3594 | 0.7196 |
race_ess:fluidity | -0.8186 | 1.5754 | -0.5196 | 0.6037 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0029 | -0.0074 | 21.0076 | 0.2786 | 0.8409 | 3 | -1319.28 | 2648.56 | 2667.01 | 128865 | 292 | 296 |
Attitudes towards multiracial adults
Findings:
- Main Effects
- Interaction
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 4.1993 | 0.5476 | 7.6681 | 0.0000 |
race_ess | -0.0723 | 0.1196 | -0.6041 | 0.5462 |
fluidity | -0.1466 | 0.1175 | -1.2479 | 0.2131 |
race_ess:fluidity | 0.0096 | 0.0258 | 0.3729 | 0.7095 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0575 | 0.0478 | 0.3444 | 5.9362 | 0.0006 | 3 | -102.494 | 214.988 | 233.44 | 34.64 | 292 | 296 |
Feeling thermometer
Findings:
- Main Effects
- Interaction
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 72.1889 | 28.9775 | 2.4912 | 0.0133 |
race_ess | -2.9928 | 6.3310 | -0.4727 | 0.6368 |
fluidity | 0.2186 | 6.2155 | 0.0352 | 0.9720 |
race_ess:fluidity | 0.4898 | 1.3667 | 0.3584 | 0.7203 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0143 | 0.0042 | 18.2248 | 1.4125 | 0.2392 | 3 | -1277.22 | 2564.43 | 2582.88 | 96985.7 | 292 | 296 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 57.2610 | 33.1556 | 1.7270 | 0.0852 |
race_ess | 0.2208 | 7.2438 | 0.0305 | 0.9757 |
fluidity | 3.6643 | 7.1117 | 0.5152 | 0.6068 |
race_ess:fluidity | -0.3546 | 1.5637 | -0.2267 | 0.8208 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0119 | 0.0017 | 20.8525 | 1.1722 | 0.3206 | 3 | -1317.08 | 2644.17 | 2662.62 | 126970 | 292 | 296 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 44.3967 | 32.7983 | 1.3536 | 0.1769 |
race_ess | 3.0538 | 7.1649 | 0.4262 | 0.6703 |
fluidity | 2.6461 | 7.0357 | 0.3761 | 0.7071 |
race_ess:fluidity | -0.3496 | 1.5467 | -0.2260 | 0.8213 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0055 | -0.0047 | 20.6241 | 0.5374 | 0.657 | 3 | -1309.38 | 2628.76 | 2647.19 | 123778 | 291 | 295 |
Authenticity
Findings:
Main Effects
Interaction
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 5.3009 | 1.5045 | 3.5232 | 0.0005 |
race_ess | -0.0593 | 0.3287 | -0.1804 | 0.8570 |
fluidity | 0.0377 | 0.3227 | 0.1168 | 0.9071 |
race_ess:fluidity | -0.0073 | 0.0710 | -0.1027 | 0.9183 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0083 | -0.0019 | 0.9463 | 0.8108 | 0.4887 | 3 | -401.64 | 813.28 | 831.732 | 261.456 | 292 | 296 |
Race & political orientation
From preregistration: Additionally, we will conduct exploratory analyses to examine whether participants’ responses vary by participant race and political orientation..
White | Black | Latine | Asian | Native | Other |
---|---|---|---|---|---|
126 | 17 | 21 | 104 | 1 | 23 |
Speeded trust task with White/Multiracial trust diff score as outcome + fluidity, race essentialism, and interaction as predictors
From preregistration:
For the speeded trust task, we will again use the White/Multiracial trust difference score as described above. We then will fit a linear regression model with the White/Multiracial trust difference score as the outcome and perceptions of multiracial identity fluidity, participant race, and the interaction term between them (i.e., perceptions of multiracial identity fluidity x participant race) as predictors.
We will also fit a linear regression model with the White/Multiracial trust difference score as the outcome and perceptions of multiracial identity fluidity, participant political orientation, and the interaction term between them (i.e., perceptions of multiracial identity fluidity x political orientation) as predictors. If we find that either of the interactions are significant, we will conduct simple slopes analysis to probe the interaction.
Findings:
Main Effects
Interactions
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | -0.1382 | 0.4205 | -0.3286 | 0.7427 |
fluidity | 0.0168 | 0.0847 | 0.1983 | 0.8429 |
race_factor1 | -0.3631 | 0.3127 | -1.1612 | 0.2465 |
race_factor2 | 0.5411 | 0.1935 | 2.7959 | 0.0055 |
race_factor3 | -0.0308 | 0.0839 | -0.3665 | 0.7142 |
race_factor4 | -0.2781 | 0.4823 | -0.5767 | 0.5646 |
race_factor5 | -0.0002 | 0.0215 | -0.0102 | 0.9918 |
fluidity:race_factor1 | 0.0506 | 0.0667 | 0.7587 | 0.4487 |
fluidity:race_factor2 | -0.1165 | 0.0417 | -2.7972 | 0.0055 |
fluidity:race_factor3 | 0.0215 | 0.0183 | 1.1752 | 0.2409 |
fluidity:race_factor4 | 0.0583 | 0.0955 | 0.6106 | 0.5420 |
fluidity:race_factor5 | NA | NA | NA | NA |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0997 | 0.0675 | 0.3884 | 3.0995 | 0.0009 | 10 | -132.116 | 288.232 | 332.312 | 42.2438 | 280 | 291 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | -0.4074 | 0.3336 | -1.2212 | 0.2230 |
fluidity | 0.0429 | 0.0718 | 0.5975 | 0.5506 |
pol_or | 0.1323 | 0.1004 | 1.3170 | 0.1889 |
fluidity:pol_or | -0.0114 | 0.0221 | -0.5185 | 0.6045 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0654 | 0.0558 | 0.389 | 6.8109 | 0.0002 | 3 | -138.526 | 287.052 | 305.504 | 44.1887 | 292 | 296 |
Other main DVs by condition + participant race and political orientation as moderators
From preregistration:
For each of the five other dependent variables, we will fit an individual linear regression model including perceptions of multiracial identity fluidity, participant race, and the interaction term (i.e., perceptions of multiracial identity fluidity x participant race) as predictors.
Again for each of the five other dependent variables, we will also fit an individual linear regression model including perceptions of multiracial identity fluidity, participant political orientation, and the interaction term (i.e., perceptions of multiracial identity fluidity x political orientation) as predictors. If we find a significant effect for either of the interaction terms for any of the models, we will conduct simple slopes analysis for that model to probe the interaction.
Trust survey
Findings:
Main Effects
Interactions
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 4.6505 | 0.8913 | 5.2177 | 0.0000 |
fluidity | 0.1030 | 0.1796 | 0.5732 | 0.5669 |
race_factor1 | 0.3482 | 0.6629 | 0.5253 | 0.5998 |
race_factor2 | -0.7195 | 0.4102 | -1.7541 | 0.0805 |
race_factor3 | -0.1894 | 0.1779 | -1.0642 | 0.2881 |
race_factor4 | 0.1242 | 1.0223 | 0.1215 | 0.9034 |
race_factor5 | -0.0360 | 0.0457 | -0.7890 | 0.4308 |
fluidity:race_factor1 | -0.1022 | 0.1414 | -0.7230 | 0.4703 |
fluidity:race_factor2 | 0.1555 | 0.0883 | 1.7606 | 0.0794 |
fluidity:race_factor3 | 0.0322 | 0.0388 | 0.8312 | 0.4066 |
fluidity:race_factor4 | 0.0501 | 0.2025 | 0.2474 | 0.8048 |
fluidity:race_factor5 | NA | NA | NA | NA |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0679 | 0.0346 | 0.8234 | 2.0383 | 0.0297 | 10 | -350.744 | 725.487 | 769.567 | 189.816 | 280 | 291 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 5.8352 | 0.6961 | 8.3825 | 0.0000 |
fluidity | -0.1047 | 0.1498 | -0.6989 | 0.4852 |
pol_or | -0.3678 | 0.2096 | -1.7549 | 0.0803 |
fluidity:pol_or | 0.0430 | 0.0460 | 0.9339 | 0.3512 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0754 | 0.0659 | 0.8117 | 7.9376 | 0 | 3 | -356.242 | 722.483 | 740.935 | 192.389 | 292 | 296 |
Trust Thermometer
Findings:
Main Effects
Interactions
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 48.6348 | 19.5518 | 2.4875 | 0.0134 |
fluidity | 5.2454 | 3.9405 | 1.3312 | 0.1842 |
race_factor1 | -20.0242 | 14.5418 | -1.3770 | 0.1696 |
race_factor2 | 3.7397 | 8.9985 | 0.4156 | 0.6780 |
race_factor3 | -2.7102 | 3.9034 | -0.6943 | 0.4881 |
race_factor4 | -12.9498 | 22.4267 | -0.5774 | 0.5641 |
race_factor5 | 0.7531 | 1.0015 | 0.7520 | 0.4527 |
fluidity:race_factor1 | 3.9539 | 3.1015 | 1.2748 | 0.2034 |
fluidity:race_factor2 | -0.7270 | 1.9371 | -0.3753 | 0.7077 |
fluidity:race_factor3 | 0.2459 | 0.8510 | 0.2889 | 0.7729 |
fluidity:race_factor4 | 3.8845 | 4.4419 | 0.8745 | 0.3826 |
fluidity:race_factor5 | NA | NA | NA | NA |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0836 | 0.0509 | 18.0616 | 2.5551 | 0.0057 | 10 | -1249.4 | 2522.79 | 2566.87 | 91342.2 | 280 | 291 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 47.2002 | 20.7599 | 2.2736 | 0.0237 |
fluidity | 5.6002 | 4.1839 | 1.3385 | 0.1818 |
race_factor1 | -13.7468 | 15.4403 | -0.8903 | 0.3741 |
race_factor2 | 8.6560 | 9.5545 | 0.9060 | 0.3657 |
race_factor3 | -7.9119 | 4.1445 | -1.9090 | 0.0573 |
race_factor4 | -16.8189 | 23.8124 | -0.7063 | 0.4806 |
race_factor5 | 0.3059 | 1.0634 | 0.2877 | 0.7738 |
fluidity:race_factor1 | 3.8135 | 3.2932 | 1.1580 | 0.2479 |
fluidity:race_factor2 | -2.0249 | 2.0568 | -0.9845 | 0.3257 |
fluidity:race_factor3 | 0.9713 | 0.9035 | 1.0750 | 0.2833 |
fluidity:race_factor4 | 4.6190 | 4.7164 | 0.9794 | 0.3283 |
fluidity:race_factor5 | NA | NA | NA | NA |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.1355 | 0.1047 | 19.1776 | 4.3903 | 0 | 10 | -1266.84 | 2557.69 | 2601.77 | 102978 | 280 | 291 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 31.3864 | 21.7917 | 1.4403 | 0.1509 |
fluidity | 7.0698 | 4.3919 | 1.6097 | 0.1086 |
race_factor1 | -44.5872 | 16.2077 | -2.7510 | 0.0063 |
race_factor2 | 6.9090 | 10.0293 | 0.6889 | 0.4915 |
race_factor3 | 2.0674 | 4.3505 | 0.4752 | 0.6350 |
race_factor4 | -23.7697 | 24.9960 | -0.9509 | 0.3425 |
race_factor5 | 0.5230 | 1.1162 | 0.4686 | 0.6398 |
fluidity:race_factor1 | 7.5351 | 3.4569 | 2.1798 | 0.0301 |
fluidity:race_factor2 | -1.4885 | 2.1591 | -0.6894 | 0.4911 |
fluidity:race_factor3 | -0.2292 | 0.9485 | -0.2416 | 0.8093 |
fluidity:race_factor4 | 6.4433 | 4.9508 | 1.3015 | 0.1942 |
fluidity:race_factor5 | NA | NA | NA | NA |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.1035 | 0.0715 | 20.1308 | 3.2317 | 0.0006 | 10 | -1280.96 | 2585.92 | 2630 | 113470 | 280 | 291 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 76.0190 | 15.8286 | 4.8026 | 0.0000 |
fluidity | -0.4736 | 3.4058 | -0.1391 | 0.8895 |
pol_or | -3.3876 | 4.7658 | -0.7108 | 0.4778 |
fluidity:pol_or | 0.2939 | 1.0471 | 0.2807 | 0.7791 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0215 | 0.0114 | 18.4569 | 2.1348 | 0.0959 | 3 | -1280.96 | 2571.92 | 2590.38 | 99471.7 | 292 | 296 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 73.5430 | 17.0221 | 4.3204 | 0.0000 |
fluidity | 0.5802 | 3.6626 | 0.1584 | 0.8742 |
pol_or | -3.9956 | 5.1252 | -0.7796 | 0.4363 |
fluidity:pol_or | 0.1129 | 1.1260 | 0.1003 | 0.9202 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0518 | 0.042 | 19.8485 | 5.3144 | 0.0014 | 3 | -1302.48 | 2614.96 | 2633.41 | 115037 | 292 | 296 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 55.5588 | 17.9492 | 3.0953 | 0.0022 |
fluidity | 0.6362 | 3.8621 | 0.1647 | 0.8693 |
pol_or | 3.4770 | 5.4043 | 0.6434 | 0.5205 |
fluidity:pol_or | -0.4421 | 1.1874 | -0.3723 | 0.7099 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0102 | 0.0001 | 20.9296 | 1.0079 | 0.3896 | 3 | -1318.18 | 2646.35 | 2664.8 | 127910 | 292 | 296 |
Attitudes towards multiracial adults
Findings:
Main Effects
Interactions
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 3.8427 | 0.3731 | 10.3000 | 0.0000 |
fluidity | -0.0932 | 0.0752 | -1.2397 | 0.2161 |
race_factor1 | -0.1379 | 0.2775 | -0.4969 | 0.6196 |
race_factor2 | 0.0024 | 0.1717 | 0.0141 | 0.9888 |
race_factor3 | -0.0291 | 0.0745 | -0.3905 | 0.6965 |
race_factor4 | 0.0107 | 0.4279 | 0.0251 | 0.9800 |
race_factor5 | 0.0209 | 0.0191 | 1.0936 | 0.2751 |
fluidity:race_factor1 | 0.0096 | 0.0592 | 0.1625 | 0.8710 |
fluidity:race_factor2 | 0.0041 | 0.0370 | 0.1097 | 0.9127 |
fluidity:race_factor3 | 0.0082 | 0.0162 | 0.5047 | 0.6142 |
fluidity:race_factor4 | 0.0040 | 0.0848 | 0.0469 | 0.9626 |
fluidity:race_factor5 | NA | NA | NA | NA |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0784 | 0.0454 | 0.3446 | 2.3805 | 0.0101 | 10 | -97.3198 | 218.64 | 262.719 | 33.2585 | 280 | 291 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 4.4882 | 0.2933 | 15.3046 | 0.0000 |
fluidity | -0.2226 | 0.0631 | -3.5269 | 0.0005 |
pol_or | -0.1980 | 0.0883 | -2.2420 | 0.0257 |
fluidity:pol_or | 0.0392 | 0.0194 | 2.0206 | 0.0442 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.071 | 0.0614 | 0.342 | 7.4346 | 0.0001 | 3 | -100.362 | 210.724 | 229.176 | 34.1446 | 292 | 296 |
## JOHNSON-NEYMAN INTERVAL
##
## When pol_or is OUTSIDE the interval [4.05, 106.89], the slope of fluidity
## is p < .05.
##
## Note: The range of observed values of pol_or is [1.00, 7.00]
##
## SIMPLE SLOPES ANALYSIS
##
## Slope of fluidity when pol_or = 1.69908 (- 1 SD):
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## -0.16 0.04 -4.41 0.00
##
## Slope of fluidity when pol_or = 2.96622 (Mean):
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## -0.11 0.03 -4.25 0.00
##
## Slope of fluidity when pol_or = 4.23335 (+ 1 SD):
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## -0.06 0.03 -1.63 0.10
ATMA Psychological Adjustment Subscale
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 4.7637 | 0.3568 | 13.3501 | 0.0000 |
fluidity | -0.2427 | 0.0768 | -3.1616 | 0.0017 |
pol_or | -0.2730 | 0.1074 | -2.5412 | 0.0116 |
fluidity:pol_or | 0.0527 | 0.0236 | 2.2319 | 0.0264 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0486 | 0.0388 | 0.4161 | 4.9725 | 0.0022 | 3 | -158.434 | 326.868 | 345.32 | 50.551 | 292 | 296 |
## JOHNSON-NEYMAN INTERVAL
##
## When pol_or is OUTSIDE the interval [3.41, 17.15], the slope of fluidity is
## p < .05.
##
## Note: The range of observed values of pol_or is [1.00, 7.00]
##
## SIMPLE SLOPES ANALYSIS
##
## Slope of fluidity when pol_or = 1.69908 (- 1 SD):
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## -0.15 0.04 -3.56 0.00
##
## Slope of fluidity when pol_or = 2.96622 (Mean):
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## -0.09 0.03 -2.84 0.00
##
## Slope of fluidity when pol_or = 4.23335 (+ 1 SD):
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## -0.02 0.04 -0.47 0.64
Feeling thermometer
Findings:
Main Effects
Interactions
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 54.2958 | 18.6984 | 2.9038 | 0.0040 |
fluidity | 4.9211 | 3.7685 | 1.3059 | 0.1927 |
race_factor1 | 0.3134 | 13.9070 | 0.0225 | 0.9820 |
race_factor2 | -2.8794 | 8.6057 | -0.3346 | 0.7382 |
race_factor3 | -7.4152 | 3.7330 | -1.9864 | 0.0480 |
race_factor4 | -11.2641 | 21.4478 | -0.5252 | 0.5999 |
race_factor5 | 0.8069 | 0.9578 | 0.8424 | 0.4003 |
fluidity:race_factor1 | 0.8828 | 2.9662 | 0.2976 | 0.7662 |
fluidity:race_factor2 | 0.3655 | 1.8526 | 0.1973 | 0.8437 |
fluidity:race_factor3 | 0.9834 | 0.8138 | 1.2084 | 0.2279 |
fluidity:race_factor4 | 3.3481 | 4.2481 | 0.7881 | 0.4313 |
fluidity:race_factor5 | NA | NA | NA | NA |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.1382 | 0.1075 | 17.2732 | 4.4913 | 0 | 10 | -1236.41 | 2496.82 | 2540.9 | 83542.1 | 280 | 291 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 68.8315 | 21.0340 | 3.2724 | 0.0012 |
fluidity | 1.6816 | 4.2392 | 0.3967 | 0.6919 |
race_factor1 | 4.7719 | 15.6441 | 0.3050 | 0.7606 |
race_factor2 | 4.3323 | 9.6806 | 0.4475 | 0.6548 |
race_factor3 | -12.4950 | 4.1993 | -2.9755 | 0.0032 |
race_factor4 | -2.4507 | 24.1268 | -0.1016 | 0.9192 |
race_factor5 | -0.9221 | 1.0774 | -0.8558 | 0.3928 |
fluidity:race_factor1 | 0.9889 | 3.3367 | 0.2964 | 0.7672 |
fluidity:race_factor2 | -1.7265 | 2.0840 | -0.8285 | 0.4081 |
fluidity:race_factor3 | 1.8353 | 0.9155 | 2.0047 | 0.0460 |
fluidity:race_factor4 | 1.5821 | 4.7787 | 0.3311 | 0.7408 |
fluidity:race_factor5 | NA | NA | NA | NA |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.1636 | 0.1337 | 19.4308 | 5.4756 | 0 | 10 | -1270.66 | 2565.32 | 2609.4 | 105716 | 280 | 291 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 47.8035 | 21.3145 | 2.2428 | 0.0257 |
fluidity | 3.8205 | 4.2957 | 0.8894 | 0.3746 |
race_factor1 | -38.9905 | 15.8558 | -2.4591 | 0.0145 |
race_factor2 | -4.5148 | 9.8102 | -0.4602 | 0.6457 |
race_factor3 | 3.5181 | 4.2556 | 0.8267 | 0.4091 |
race_factor4 | 7.7737 | 24.4494 | 0.3180 | 0.7508 |
race_factor5 | -0.4085 | 1.0918 | -0.3742 | 0.7086 |
fluidity:race_factor1 | 6.5543 | 3.3823 | 1.9378 | 0.0537 |
fluidity:race_factor2 | 0.4565 | 2.1120 | 0.2161 | 0.8290 |
fluidity:race_factor3 | -0.6463 | 0.9278 | -0.6966 | 0.4866 |
fluidity:race_factor4 | 0.0795 | 4.8426 | 0.0164 | 0.9869 |
fluidity:race_factor5 | NA | NA | NA | NA |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.1174 | 0.0858 | 19.6899 | 3.7124 | 0.0001 | 10 | -1270.12 | 2564.23 | 2608.27 | 108166 | 279 | 290 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 96.5667 | 15.1918 | 6.3565 | 0.0000 |
fluidity | -3.8549 | 3.2688 | -1.1793 | 0.2392 |
pol_or | -11.3705 | 4.5741 | -2.4859 | 0.0135 |
fluidity:pol_or | 1.8412 | 1.0049 | 1.8321 | 0.0680 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0687 | 0.0592 | 17.7143 | 7.1856 | 0.0001 | 3 | -1268.81 | 2547.61 | 2566.07 | 91628.7 | 292 | 296 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 87.1326 | 17.4661 | 4.9887 | 0.0000 |
fluidity | -1.8632 | 3.7582 | -0.4958 | 0.6204 |
pol_or | -8.3622 | 5.2588 | -1.5901 | 0.1129 |
fluidity:pol_or | 1.0599 | 1.1554 | 0.9174 | 0.3597 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0574 | 0.0478 | 20.3662 | 5.9326 | 0.0006 | 3 | -1310.1 | 2630.2 | 2648.65 | 121117 | 292 | 296 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 70.1508 | 17.7181 | 3.9593 | 0.0001 |
fluidity | -1.6856 | 3.8139 | -0.4419 | 0.6589 |
pol_or | -3.7813 | 5.3333 | -0.7090 | 0.4789 |
fluidity:pol_or | 0.8560 | 1.1719 | 0.7304 | 0.4657 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.003 | -0.0073 | 20.6504 | 0.2894 | 0.833 | 3 | -1309.75 | 2629.51 | 2647.94 | 124094 | 291 | 295 |
Authenticity
Findings:
- Main Effects
- Interactions White, Black, Latine,
Asian, Native and Other
Estimates for the authenticity model with race term estimate std.error statistic p.value (Intercept) 4.0860 0.9753 4.1895 0.0000 fluidity 0.2461 0.1966 1.2521 0.2116 race_factor1 -0.2819 0.7254 -0.3886 0.6979 race_factor2 -0.3312 0.4489 -0.7379 0.4612 race_factor3 -0.2003 0.1947 -1.0288 0.3045 race_factor4 -0.9625 1.1187 -0.8604 0.3903 race_factor5 -0.0352 0.0500 -0.7055 0.4811 fluidity:race_factor1 -0.0394 0.1547 -0.2547 0.7992 fluidity:race_factor2 0.0913 0.0966 0.9448 0.3456 fluidity:race_factor3 0.0368 0.0424 0.8675 0.3864 fluidity:race_factor4 0.2749 0.2216 1.2407 0.2157 fluidity:race_factor5 NA NA NA NA
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.1196 | 0.0882 | 0.9009 | 3.805 | 0.0001 | 10 | -376.949 | 777.897 | 821.977 | 227.274 | 280 | 291 |
term | estimate | std.error | statistic | p.value |
---|---|---|---|---|
(Intercept) | 5.2038 | 0.7986 | 6.5158 | 0.0000 |
fluidity | 0.0689 | 0.1718 | 0.4011 | 0.6886 |
pol_or | -0.0129 | 0.2405 | -0.0536 | 0.9573 |
fluidity:pol_or | -0.0302 | 0.0528 | -0.5713 | 0.5682 |
r.squared | adj.r.squared | sigma | statistic | p.value | df | logLik | AIC | BIC | deviance | df.residual | nobs |
---|---|---|---|---|---|---|---|---|---|---|---|
0.0395 | 0.0296 | 0.9312 | 3.9996 | 0.0082 | 3 | -396.908 | 803.816 | 822.268 | 253.229 | 292 | 296 |
Descriptives by race
White:
Table continues below vars n mean sd median whitemulti_trust_dif 1 126 0.006029 0.3691 0.025 White 2 126 2.926 0.5437 2.9 Multiracial 3 126 2.92 0.5133 2.875 Black 4 126 3.195 0.5396 3.225 trust_survey 5 126 4.977 0.8474 4.95 trust_therm_multiracial 6 126 70.37 17.87 70 trust_therm_black 7 126 68.75 18.74 70 trust_therm_white 8 126 67.01 20.67 70 atma 9 126 3.443 0.3718 3.435 feel_therm_multiracial 10 126 71.79 16.95 71 feel_therm_black 11 126 71.13 18.22 71 feel_therm_white 12 125 68.7 18.28 67 authen 13 126 5.371 0.8987 5.5 race_ess 14 126 4.008 0.9203 4.125 pol_or 15 126 2.762 1.293 2 Table continues below trimmed mad min max range whitemulti_trust_dif 0.01284 0.3336 -1.05 0.925 1.975 White 2.89 0.4448 1.9 5 3.1 Multiracial 2.901 0.3839 1.625 4.85 3.225 Black 3.199 0.4448 1.525 4.95 3.425 trust_survey 4.925 1.26 3.4 6.8 3.4 trust_therm_multiracial 69.65 25.2 37 100 63 trust_therm_black 68.27 28.17 31 100 69 trust_therm_white 67.25 28.91 1 100 99 atma 3.438 0.419 2.435 4.391 1.957 feel_therm_multiracial 71.06 20.76 48 100 52 feel_therm_black 70.58 27.43 35 100 65 feel_therm_white 68.49 25.2 25 100 75 authen 5.373 1.112 3.25 7 3.75 race_ess 4.047 0.9266 1.5 6.125 4.625 pol_or 2.667 1.483 1 7 6 skew kurtosis se whitemulti_trust_dif -0.2261 0.5646 0.03288 White 0.8409 1.316 0.04843 Multiracial 0.6447 1.972 0.04572 Black -0.05767 1.195 0.04807 trust_survey 0.2307 -1.12 0.07549 trust_therm_multiracial 0.1809 -1.175 1.592 trust_therm_black 0.2215 -1.027 1.67 trust_therm_white -0.1804 -0.3164 1.841 atma 0.1067 -0.3087 0.03313 feel_therm_multiracial 0.2099 -1.172 1.51 feel_therm_black 0.1763 -1.246 1.623 feel_therm_white 0.05086 -0.9255 1.635 authen -0.113 -0.9182 0.08007 race_ess -0.3509 -0.1315 0.08199 pol_or 0.6647 -0.1207 0.1152 Black:
Table continues below vars n mean sd median trimmed whitemulti_trust_dif 1 17 -0.2352 0.361 -0.275 -0.2683 White 2 17 2.429 0.6991 2.45 2.363 Multiracial 3 17 2.664 0.6198 2.7 2.601 Black 4 17 3.31 0.6742 3.375 3.294 trust_survey 5 16 4.719 0.969 4.15 4.664 trust_therm_multiracial 6 16 66.69 23.47 72 67.5 trust_therm_black 7 16 76.38 18.45 81.5 76.93 trust_therm_white 8 16 46.94 23.08 47.5 47.07 atma 9 16 3.236 0.38 3.196 3.217 feel_therm_multiracial 10 16 80.5 15.73 80 81.29 feel_therm_black 11 16 89.69 13.12 95.5 90.79 feel_therm_white 12 16 51.12 21.82 50.5 50.43 authen 13 16 4.422 1.094 4.375 4.375 race_ess 14 16 4.164 1.044 4.25 4.214 pol_or 15 17 2.529 1.179 2 2.467 Table continues below mad min max range skew whitemulti_trust_dif 0.1853 -0.8476 0.875 1.723 1.306 White 0.6672 1.35 4.5 3.15 1.218 Multiracial 0.3706 1.775 4.5 2.725 1.168 Black 0.5189 2.15 4.7 2.55 0.06151 trust_survey 0.6672 3.5 6.7 3.2 0.6638 trust_therm_multiracial 26.69 22 100 78 -0.3558 trust_therm_black 13.34 45 100 55 -0.5612 trust_therm_white 29.65 2 90 88 -0.03617 atma 0.3868 2.652 4.087 1.435 0.4916 feel_therm_multiracial 14.83 50 100 50 -0.5293 feel_therm_black 6.672 64 100 36 -0.9017 feel_therm_white 17.79 17 95 78 0.3396 authen 0.9266 3 6.5 3.5 0.5685 race_ess 1.019 2 5.625 3.625 -0.5972 pol_or 1.483 1 5 4 0.4726 kurtosis se whitemulti_trust_dif 2.94 0.08755 White 2.057 0.1696 Multiracial 2.075 0.1503 Black -0.6345 0.1635 trust_survey -0.9581 0.2422 trust_therm_multiracial -1.023 5.866 trust_therm_black -1.108 4.612 trust_therm_white -0.8673 5.771 atma -0.5649 0.09501 feel_therm_multiracial -0.7136 3.933 feel_therm_black -0.9783 3.28 feel_therm_white -0.8528 5.454 authen -0.7522 0.2736 race_ess -0.6211 0.2609 pol_or -0.9167 0.2859 Latine:
Table continues below vars n mean sd median whitemulti_trust_dif 1 21 -0.09643 0.6531 0.075 White 2 21 2.673 0.5521 2.8 Multiracial 3 21 2.769 0.4421 2.875 Black 4 21 3.063 0.6533 3.125 trust_survey 5 21 4.824 0.7943 4.7 trust_therm_multiracial 6 21 69.48 20.51 71 trust_therm_black 7 21 70.52 22.55 75 trust_therm_white 8 21 56.71 26.22 50 atma 9 21 3.402 0.3233 3.348 feel_therm_multiracial 10 21 72.43 19.39 70 feel_therm_black 11 21 69.71 23.28 71 feel_therm_white 12 21 52.05 29.72 50 authen 13 21 5.155 0.7561 5.25 race_ess 14 21 4.643 0.9128 4.75 pol_or 15 21 3 1.414 2 Table continues below trimmed mad min max range whitemulti_trust_dif -0.004412 0.556 -1.95 0.675 2.625 White 2.681 0.2965 1.525 3.725 2.2 Multiracial 2.771 0.6301 2.075 3.475 1.4 Black 3.101 0.6672 1.75 4.025 2.275 trust_survey 4.771 1.038 3.9 6.2 2.3 trust_therm_multiracial 70.47 20.76 27 100 73 trust_therm_black 72 22.24 16 100 84 trust_therm_white 57.29 34.1 10 100 90 atma 3.361 0.2578 2.957 4.217 1.261 feel_therm_multiracial 72.65 22.24 36 100 64 feel_therm_black 71.47 28.17 13 100 87 feel_therm_white 51.94 29.65 1 100 99 authen 5.088 0.7413 4 7 3 race_ess 4.662 0.9266 2.875 6.25 3.375 pol_or 2.824 1.483 1 6 5 skew kurtosis se whitemulti_trust_dif -1.179 0.8813 0.1425 White -0.3122 -0.4768 0.1205 Multiracial -0.02001 -1.384 0.09647 Black -0.4964 -0.8308 0.1426 trust_survey 0.3527 -1.421 0.1733 trust_therm_multiracial -0.2743 -0.7724 4.475 trust_therm_black -0.4981 -0.5823 4.921 trust_therm_white -0.05948 -1.235 5.721 atma 1.015 0.6112 0.07055 feel_therm_multiracial -0.005503 -1.221 4.232 feel_therm_black -0.5795 -0.3346 5.081 feel_therm_white 0.1886 -1.148 6.485 authen 0.6786 -0.1575 0.165 race_ess -0.07901 -0.4858 0.1992 pol_or 0.8081 -0.5238 0.3086 Asian:
Table continues below vars n mean sd median trimmed whitemulti_trust_dif 1 104 0.1489 0.3508 0.1439 0.1465 White 2 104 2.982 0.4748 3 2.976 Multiracial 3 104 2.833 0.4667 2.85 2.825 Black 4 104 2.932 0.5306 2.95 2.922 trust_survey 5 104 4.651 0.773 4.5 4.596 trust_therm_multiracial 6 104 61.91 16.52 55 60.9 trust_therm_black 7 104 57.08 19.5 50 56.6 trust_therm_white 8 104 60.57 16.74 59.5 60.52 atma 9 104 3.405 0.32 3.391 3.403 feel_therm_multiracial 10 104 62.37 17.43 58 61.64 feel_therm_black 11 104 59.33 20.52 56 59.2 feel_therm_white 12 104 58.9 17.85 55 58.46 authen 13 104 4.841 0.8455 4.875 4.836 race_ess 14 104 4.453 0.8597 4.375 4.435 pol_or 15 104 3.279 1.144 4 3.31 Table continues below mad min max range skew whitemulti_trust_dif 0.3706 -0.7 1.025 1.725 0.05244 White 0.4633 1.875 4.225 2.35 0.09718 Multiracial 0.5189 1.875 4.5 2.625 0.3427 Black 0.4262 1.55 4.5 2.95 0.1436 trust_survey 0.7413 3.2 6.7 3.5 0.5747 trust_therm_multiracial 13.34 17 100 83 0.3752 trust_therm_black 14.83 4 100 96 0.2461 trust_therm_white 14.83 17 100 83 0.1237 atma 0.3223 2.522 4.435 1.913 0.1141 feel_therm_multiracial 13.34 22 100 78 0.3558 feel_therm_black 22.24 8 100 92 0.05048 feel_therm_white 17.05 19 100 81 0.2257 authen 0.9266 3 7 4 0.08837 race_ess 0.7413 2.25 6.625 4.375 0.2039 pol_or 1.483 1 6 5 -0.3599 kurtosis se whitemulti_trust_dif -0.1243 0.0344 White -0.1117 0.04656 Multiracial 0.4618 0.04577 Black 0.327 0.05203 trust_survey -0.288 0.0758 trust_therm_multiracial -0.1408 1.62 trust_therm_black -0.1874 1.913 trust_therm_white -0.1624 1.642 atma 0.5561 0.03138 feel_therm_multiracial -0.4251 1.709 feel_therm_black -0.5083 2.013 feel_therm_white -0.1092 1.75 authen -0.2252 0.08291 race_ess -0.304 0.0843 pol_or -0.6572 0.1122 Native:
Table continues below vars n mean sd median trimmed mad whitemulti_trust_dif 1 1 0 NA 0 0 0 White 2 1 3.775 NA 3.775 3.775 0 Multiracial 3 1 3.775 NA 3.775 3.775 0 Black 4 1 3.925 NA 3.925 3.925 0 trust_survey 5 1 6.7 NA 6.7 6.7 0 trust_therm_multiracial 6 1 100 NA 100 100 0 trust_therm_black 7 1 100 NA 100 100 0 trust_therm_white 8 1 100 NA 100 100 0 atma 9 1 3.478 NA 3.478 3.478 0 feel_therm_multiracial 10 1 100 NA 100 100 0 feel_therm_black 11 1 100 NA 100 100 0 feel_therm_white 12 1 100 NA 100 100 0 authen 13 1 7 NA 7 7 0 race_ess 14 1 4.625 NA 4.625 4.625 0 pol_or 15 1 3 NA 3 3 0 min max range skew kurtosis se whitemulti_trust_dif 0 0 0 NA NA NA White 3.775 3.775 0 NA NA NA Multiracial 3.775 3.775 0 NA NA NA Black 3.925 3.925 0 NA NA NA trust_survey 6.7 6.7 0 NA NA NA trust_therm_multiracial 100 100 0 NA NA NA trust_therm_black 100 100 0 NA NA NA trust_therm_white 100 100 0 NA NA NA atma 3.478 3.478 0 NA NA NA feel_therm_multiracial 100 100 0 NA NA NA feel_therm_black 100 100 0 NA NA NA feel_therm_white 100 100 0 NA NA NA authen 7 7 0 NA NA NA race_ess 4.625 4.625 0 NA NA NA pol_or 3 3 0 NA NA NA Other:
Table continues below vars n mean sd median trimmed whitemulti_trust_dif 1 23 -0.0663 0.3879 -0.025 -0.07368 White 2 23 2.796 0.3887 2.9 2.811 Multiracial 3 23 2.862 0.3462 2.9 2.882 Black 4 23 3.092 0.3755 3.1 3.082 trust_survey 5 23 4.917 0.8451 4.9 4.858 trust_therm_multiracial 6 23 75.17 19.28 80 75.74 trust_therm_black 7 23 73.04 17.99 75 73.16 trust_therm_white 8 23 64.7 24.81 69 65.84 atma 9 23 3.543 0.3703 3.478 3.538 feel_therm_multiracial 10 23 79.7 17.96 85 81.47 feel_therm_black 11 23 71.52 21.47 71 72.21 feel_therm_white 12 23 62.35 22.99 65 63.53 authen 13 23 4.978 1.1 4.75 4.987 race_ess 14 23 4.337 0.915 4.125 4.395 pol_or 15 23 2.783 1.413 2 2.737 Table continues below mad min max range skew whitemulti_trust_dif 0.4077 -0.775 0.775 1.55 0.08783 White 0.2965 1.925 3.475 1.55 -0.5074 Multiracial 0.2224 2.05 3.625 1.575 -0.4336 Black 0.3706 2.35 3.825 1.475 0.2688 trust_survey 1.334 4 6.4 2.4 0.2887 trust_therm_multiracial 26.69 40 100 60 -0.2967 trust_therm_black 22.24 40 100 60 -0.07306 trust_therm_white 28.17 15 100 85 -0.2087 atma 0.4512 2.957 4.174 1.217 0.1735 feel_therm_multiracial 16.31 40 100 60 -0.7723 feel_therm_black 28.17 35 100 65 -0.1524 feel_therm_white 25.2 5 100 95 -0.4287 authen 1.112 3 7 4 0.06183 race_ess 0.7413 2.375 5.625 3.25 -0.2731 pol_or 1.483 1 5 4 0.1831 kurtosis se whitemulti_trust_dif -0.4807 0.08089 White -0.6931 0.08106 Multiracial 0.2929 0.0722 Black -0.5533 0.07829 trust_survey -1.411 0.1762 trust_therm_multiracial -1.384 4.021 trust_therm_black -1.054 3.75 trust_therm_white -1.109 5.173 atma -1.35 0.07721 feel_therm_multiracial -0.5 3.745 feel_therm_black -1.325 4.477 feel_therm_white -0.3736 4.794 authen -1.176 0.2293 race_ess -0.7609 0.1908 pol_or -1.485 0.2946
Additional Exploratory Descriptives looking at Trust Therm and Feeling Therm toward White, Black, and Multiracial targets
We will also collect additional data on participant’s trust and explicit attitudes towards Black and White monoracial people. Specifically, participants will be asked to complete trust thermometers assessing their feelings of trust towards Black people and White people (on a scale from 0, very untrustworthy, to 100, very trustworthy) and feeling thermometers assessing their feelings of warmth towards Black people and White people (on a scale from 0 to 100, with higher numbers indicating more favorable feelings). We will conduct paired-samples t-tests to determine if there are any differences in participants’ feelings of trust and warmth towards Black/White multiracial people relative to monoracial Black and White people, respectively.
##
## Paired t-test
##
## data: mift2_data$trust_therm_black and mift2_data$trust_therm_multiracial
## t = -3.452, df = 295, p-value = 0.000639
## alternative hypothesis: true mean difference is not equal to 0
## 95 percent confidence interval:
## -3.055500 -0.836392
## sample estimates:
## mean difference
## -1.94595
## [1] 65.7432
## [1] 67.6892
##
## Paired t-test
##
## data: mift2_data$trust_therm_white and mift2_data$trust_therm_multiracial
## t = -4.943, df = 295, p-value = 0.00000129
## alternative hypothesis: true mean difference is not equal to 0
## 95 percent confidence interval:
## -6.62684 -2.85289
## sample estimates:
## mean difference
## -4.73986
## [1] 62.9493
## [1] 67.6892
##
## Paired t-test
##
## data: mift2_data$feel_therm_black and mift2_data$feel_therm_multiracial
## t = -2.818, df = 295, p-value = 0.00516
## alternative hypothesis: true mean difference is not equal to 0
## 95 percent confidence interval:
## -3.086862 -0.548273
## sample estimates:
## mean difference
## -1.81757
## [1] 67.8345
## [1] 69.652
##
## Paired t-test
##
## data: mift2_data$feel_therm_white and mift2_data$feel_therm_multiracial
## t = -6.592, df = 294, p-value = 0.0000000002
## alternative hypothesis: true mean difference is not equal to 0
## 95 percent confidence interval:
## -9.13814 -4.93643
## sample estimates:
## mean difference
## -7.03729
## [1] 62.5763
## [1] 69.652
Main Analyses Conducted again using the fluidity should measure
We will collect additional data on participants’ perceptions of how they think multiracial people should experience their identity (i.e., norms about identity fluidity). Participants will complete a 7-item scale assessing whether they believe that multiracial identity should be fluid. Participants will indicate their level of agreement with each of the seven statements on a scale from 1 (strongly disagree) to 7 (strongly agree). Participant’s responses will be averaged after recoding reverse scored items, with a higher score indicating greater belief that multiracial identity should be fluid. We will conduct each of our main analyses again using this multiracial identity fluidity norm score in place of the perceptions of multiracial identity fluidity score.
GEE Model for Speeded Trust Task
Findings:
xxx
## (Intercept) fluidity_should
## 2.8154364 0.0146586
## race_multi race_black
## -0.1709474 -0.1057910
## fluidity_should:race_multi fluidity_should:race_black
## 0.0315061 0.0684651
term | estimate | std.error | statistic | p.value | NA |
---|---|---|---|---|---|
(Intercept) | 2.8154 | 0.0402 | 70.0549 | 0.1397 | 20.1580 |
fluidity_should | 0.0147 | 0.0088 | 1.6676 | 0.0309 | 0.4752 |
race_multi | -0.1709 | 0.0568 | -3.0070 | 0.0975 | -1.7529 |
race_black | -0.1058 | 0.0569 | -1.8605 | 0.1390 | -0.7611 |
fluidity_should:race_multi | 0.0315 | 0.0124 | 2.5340 | 0.0221 | 1.4282 |
fluidity_should:race_black | 0.0685 | 0.0124 | 5.5049 | 0.0304 | 2.2558 |
## Estimate Naive S.E. Naive z Robust S.E. Robust z
## (Intercept) 2.8154364 0.04018902 70.05486 0.1396688 20.157950
## fluidity_should 0.0146586 0.00879047 1.66756 0.0308503 0.475153
## race_multi -0.1709474 0.05684986 -3.00700 0.0975252 -1.752854
## race_black -0.1057910 0.05686011 -1.86055 0.1389983 -0.761096
## fluidity_should:race_multi 0.0315061 0.01243327 2.53402 0.0220598 1.428216
## fluidity_should:race_black 0.0684651 0.01243712 5.50490 0.0303512 2.255766
## (Intercept)
## 0.00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000229181
## fluidity_should
## 0.63467815709249020272864072467200458049774169921875000000000000000000000000000000000000000000000
## race_multi
## 0.07962713944158993084609932111561647616326808929443359375000000000000000000000000000000000000000
## race_black
## 0.44659961837782768956373047330998815596103668212890625000000000000000000000000000000000000000000
## fluidity_should:race_multi
## 0.15322960996367368524673224783327896147966384887695312500000000000000000000000000000000000000000
## fluidity_should:race_black
## 0.02408529486438571245998652159414632478728890419006347656250000000000000000000000000000000000000
## $emtrends
## race_black fluidity_should.trend SE df asymp.LCL asymp.UCL
## 0 0.0304 0.0263 Inf -0.0212 0.082
## 1 0.0989 0.0314 Inf 0.0374 0.160
##
## Results are averaged over the levels of: race_multi
## Covariance estimate used: robust.variance
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df z.ratio p.value
## race_black0 - race_black1 -0.0685 0.0304 Inf -2.256 0.0241
##
## Results are averaged over the levels of: race_multi
Pearson correlation for trust, feeling therm, atma, and authenticty
## [1] "race_ess" "fluidity_should"
## [3] "trust_therm_multiracial" "trust_therm_black"
## [5] "trust_therm_white" "trust_survey"
## [7] "feel_therm_multiracial" "feel_therm_black"
## [9] "feel_therm_white" "atma"
## [11] "authen" "whitemulti_trust_dif"
## [13] "White" "Multiracial"
## [15] "Black"
##
## CORRELATION MATRIX
##
## Correlation Matrix
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## race_ess fluidity_should trust_therm_multiracial trust_therm_black trust_therm_white trust_survey feel_therm_multiracial feel_therm_black feel_therm_white atma authen whitemulti_trust_dif White Multiracial Black
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## race_ess Pearson's r —
## df —
## p-value —
##
## fluidity_should Pearson's r -0.247437 —
## df 294 —
## p-value 0.000017 —
##
## trust_therm_multiracial Pearson's r -0.064788 0.176418 —
## df 294 294 —
## p-value 0.266521 0.002317 —
##
## trust_therm_black Pearson's r -0.104555 0.149914 0.878947 —
## df 294 294 294 —
## p-value 0.072472 0.009797 < .000001 —
##
## trust_therm_white Pearson's r 0.016738 0.098781 0.657025 0.505089 —
## df 294 294 294 294 —
## p-value 0.774289 0.089801 < .000001 < .000001 —
##
## trust_survey Pearson's r -0.055668 0.223730 0.445001 0.438507 0.233582 —
## df 294 294 294 294 294 —
## p-value 0.339861 0.000104 < .000001 < .000001 0.000050 —
##
## feel_therm_multiracial Pearson's r -0.053409 0.177762 0.630687 0.613993 0.343857 0.405752 —
## df 294 294 294 294 294 294 —
## p-value 0.359850 0.002141 < .000001 < .000001 < .000001 < .000001 —
##
## feel_therm_black Pearson's r -0.072851 0.136992 0.618631 0.710976 0.286200 0.376972 0.847407 —
## df 294 294 294 294 294 294 294 —
## p-value 0.211398 0.018371 < .000001 < .000001 < .000001 < .000001 < .000001 —
##
## feel_therm_white Pearson's r 0.059384 0.209218 0.452510 0.339852 0.639132 0.251609 0.560170 0.441987 —
## df 293 293 293 293 293 293 293 293 —
## p-value 0.309382 0.000297 < .000001 < .000001 < .000001 0.000012 < .000001 < .000001 —
##
## atma Pearson's r -0.040402 -0.061449 0.122677 0.135770 0.124292 0.273195 0.168283 0.185392 0.187265 —
## df 294 294 294 294 294 294 294 294 293 —
## p-value 0.488661 0.292004 0.034887 0.019448 0.032545 0.000002 0.003687 0.001356 0.001232 —
##
## authen Pearson's r -0.090582 0.247855 0.355394 0.326596 0.273675 0.417898 0.273836 0.240773 0.292888 0.387133 —
## df 294 294 294 294 294 294 294 294 293 294 —
## p-value 0.119937 0.000016 < .000001 < .000001 0.000002 < .000001 0.000002 0.000028 < .000001 < .000001 —
##
## whitemulti_trust_dif Pearson's r 0.010527 -0.078632 -0.142378 -0.230193 0.191497 -0.187208 -0.214286 -0.253019 0.114861 0.039684 -0.057161 —
## df 294 294 294 294 294 294 294 294 293 294 294 —
## p-value 0.856877 0.177274 0.014218 0.000064 0.000928 0.001213 0.000204 0.000011 0.048729 0.496421 0.327046 —
##
## White Pearson's r -0.072493 0.032253 0.158602 0.068181 0.353758 0.010237 -0.044260 -0.082720 0.227702 0.100937 0.171766 0.482815 —
## df 294 294 294 294 294 294 294 294 293 294 294 295 —
## p-value 0.213653 0.580470 0.006248 0.242231 < .000001 0.860780 0.448077 0.155727 0.000079 0.082977 0.003029 < .000001 —
##
## Multiracial Pearson's r -0.088332 0.100812 0.292529 0.266323 0.229023 0.166962 0.129666 0.119668 0.154471 0.077786 0.236094 -0.287890 0.699650 —
## df 294 294 294 294 294 294 294 294 293 294 294 295 295 —
## p-value 0.129457 0.083361 < .000001 0.000003 0.000070 0.003969 0.025691 0.039635 0.007865 0.181991 0.000041 < .000001 < .000001 —
##
## Black Pearson's r -0.143572 0.164168 0.325780 0.383333 0.061726 0.253491 0.225099 0.287060 0.037957 0.169317 0.304808 -0.324099 0.387644 0.688342 —
## df 294 294 294 294 294 294 294 294 293 294 294 295 295 295 —
## p-value 0.013418 0.004629 < .000001 < .000001 0.289829 0.000010 0.000094 < .000001 0.516077 0.003480 < .000001 < .000001 < .000001 < .000001 —
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Non-preregistered Analyses
Examining the Attitudes Towards Multiracial Adults scale by subscale
It appears that it is the self-esteem subscale that is driving any marginal by-condition differens as this is the only significant t-test between conditions
Self-esteem subscale
Test statistic | df | P value | Alternative hypothesis | cor |
---|---|---|---|---|
-6.557 | 294 | 0.0000000002462 * * * | two.sided | -0.3572 |
Test statistic | df | P value | Alternative hypothesis | cor |
---|---|---|---|---|
-2.999 | 294 | 0.002943 * * | two.sided | -0.1723 |
Multiracial Heritage subscale
Test statistic | df | P value | Alternative hypothesis | cor |
---|---|---|---|---|
-2.122 | 294 | 0.03465 * | two.sided | -0.1228 |
Test statistic | df | P value | Alternative hypothesis | cor |
---|---|---|---|---|
-0.05415 | 294 | 0.9569 | two.sided | -0.003158 |
Psychological Adjustment subscale
Test statistic | df | P value | Alternative hypothesis | cor |
---|---|---|---|---|
-2.477 | 294 | 0.01382 * | two.sided | -0.143 |
Test statistic | df | P value | Alternative hypothesis | cor |
---|---|---|---|---|
0.02066 | 294 | 0.9835 | two.sided | 0.001205 |
Multiracial Identity subscale
Test statistic | df | P value | Alternative hypothesis | cor |
---|---|---|---|---|
0.7016 | 294 | 0.4835 | two.sided | 0.04088 |
Test statistic | df | P value | Alternative hypothesis | cor |
---|---|---|---|---|
0.05446 | 294 | 0.9566 | two.sided | 0.003176 |
Main Analyses Again by Race
Fluidity
White participants
GEE Model for Speeded Trust Task
## (Intercept) fluidity race_multi race_black
## 2.96686614 -0.00905379 0.00985479 0.14263618
## fluidity:race_multi fluidity:race_black
## -0.00359068 0.02812976
term | estimate | std.error | statistic | p.value | NA |
---|---|---|---|---|---|
(Intercept) | 2.9669 | 0.0906 | 32.7291 | 0.2812 | 10.5498 |
fluidity | -0.0091 | 0.0200 | -0.4536 | 0.0607 | -0.1492 |
race_multi | 0.0099 | 0.1283 | 0.0768 | 0.2026 | 0.0486 |
race_black | 0.1426 | 0.1283 | 1.1116 | 0.2763 | 0.5162 |
fluidity:race_multi | -0.0036 | 0.0282 | -0.1271 | 0.0437 | -0.0821 |
fluidity:race_black | 0.0281 | 0.0283 | 0.9956 | 0.0599 | 0.4693 |
## Estimate Naive S.E. Naive z Robust S.E. Robust z
## (Intercept) 2.96686614 0.0906493 32.7290677 0.2812236 10.5498484
## fluidity -0.00905379 0.0199584 -0.4536324 0.0606822 -0.1492002
## race_multi 0.00985479 0.1282849 0.0768196 0.2025831 0.0486457
## race_black 0.14263618 0.1283142 1.1116167 0.2763054 0.5162265
## fluidity:race_multi -0.00359068 0.0282486 -0.1271102 0.0437490 -0.0820747
## fluidity:race_black 0.02812976 0.0282531 0.9956348 0.0599384 0.4693112
## (Intercept) fluidity
## 0.0000000000000000000000000508791 0.8813956974922111387016343542200
## race_multi race_black
## 0.9612016625875968722780839925690 0.6056962297667645156451499133254
## fluidity:race_multi fluidity:race_black
## 0.9345872807885975408481726844911 0.6388472115790697625214988875086
Pearson correlation for trust, feeling therm, atma, and authenticty
## [1] "race_ess" "fluidity"
## [3] "trust_therm_multiracial" "trust_therm_black"
## [5] "trust_therm_white" "trust_survey"
## [7] "feel_therm_multiracial" "feel_therm_black"
## [9] "feel_therm_white" "atma"
## [11] "authen" "whitemulti_trust_dif"
## [13] "White" "Multiracial"
## [15] "Black"
##
## CORRELATION MATRIX
##
## Correlation Matrix
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## race_ess fluidity trust_therm_multiracial trust_therm_black trust_therm_white trust_survey feel_therm_multiracial feel_therm_black feel_therm_white atma authen whitemulti_trust_dif White Multiracial Black
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## race_ess Pearson's r —
## df —
## p-value —
##
## fluidity Pearson's r -0.214494 —
## df 124 —
## p-value 0.015872 —
##
## trust_therm_multiracial Pearson's r 0.071804 -0.091815 —
## df 124 124 —
## p-value 0.424291 0.306537 —
##
## trust_therm_black Pearson's r 0.052926 -0.073735 0.928517 —
## df 124 124 124 —
## p-value 0.556142 0.411909 < .000001 —
##
## trust_therm_white Pearson's r 0.032490 -0.195169 0.725720 0.678889 —
## df 124 124 124 124 —
## p-value 0.717981 0.028521 < .000001 < .000001 —
##
## trust_survey Pearson's r 0.056400 -0.029911 0.265421 0.312712 0.135040 —
## df 124 124 124 124 124 —
## p-value 0.530479 0.739525 0.002667 0.000364 0.131649 —
##
## feel_therm_multiracial Pearson's r 0.124000 -0.030191 0.550884 0.504880 0.350299 0.375184 —
## df 124 124 124 124 124 124 —
## p-value 0.166551 0.737182 < .000001 < .000001 0.000058 0.000015 —
##
## feel_therm_black Pearson's r 0.145482 -0.042577 0.616282 0.622130 0.431740 0.345020 0.854440 —
## df 124 124 124 124 124 124 124 —
## p-value 0.104074 0.635946 < .000001 < .000001 < .000001 0.000076 < .000001 —
##
## feel_therm_white Pearson's r 0.166641 -0.111662 0.466953 0.413571 0.495416 0.313951 0.774831 0.676444 —
## df 123 123 123 123 123 123 123 123 —
## p-value 0.063256 0.215066 < .000001 0.000002 < .000001 0.000363 < .000001 < .000001 —
##
## atma Pearson's r 0.001085 -0.248797 0.112446 0.139617 0.093503 0.243322 0.219093 0.253000 0.221969 —
## df 124 124 124 124 124 124 124 124 123 —
## p-value 0.990380 0.004966 0.209986 0.118944 0.297693 0.006043 0.013708 0.004260 0.012851 —
##
## authen Pearson's r -0.086408 -0.101602 0.278317 0.302624 0.112794 0.440923 0.289697 0.233963 0.184509 0.444390 —
## df 124 124 124 124 124 124 124 124 123 124 —
## p-value 0.336019 0.257615 0.001602 0.000573 0.208570 < .000001 0.001001 0.008370 0.039411 < .000001 —
##
## whitemulti_trust_dif Pearson's r -0.009522 0.006105 -0.054158 -0.092074 0.130378 -0.085131 -0.094624 -0.095560 0.031214 0.000572 -0.027690 —
## df 124 124 124 124 124 124 124 124 123 124 124 —
## p-value 0.915722 0.945907 0.546973 0.305169 0.145636 0.343238 0.291911 0.287147 0.729676 0.994929 0.758251 —
##
## White Pearson's r -0.113795 -0.013023 0.240592 0.195180 0.318320 0.050998 0.010358 0.000647 0.121398 0.065059 0.210614 0.419588 —
## df 124 124 124 124 124 124 124 124 123 124 124 124 —
## p-value 0.204535 0.884921 0.006654 0.028512 0.000281 0.570633 0.908352 0.994263 0.177456 0.469208 0.017924 0.000001 —
##
## Multiracial Pearson's r -0.113693 -0.018186 0.293804 0.272968 0.243427 0.115245 0.079024 0.069409 0.106294 0.068504 0.243013 -0.274709 0.757528 —
## df 124 124 124 124 124 124 124 124 123 124 124 124 124 —
## p-value 0.204943 0.839825 0.000841 0.001985 0.006020 0.198785 0.379089 0.439947 0.238074 0.445947 0.006109 0.001852 < .000001 —
##
## Black Pearson's r -0.084546 0.026060 0.259290 0.267095 0.057300 0.130368 0.064444 0.115749 0.032938 0.098120 0.221694 -0.293486 0.530366 0.772875 —
## df 124 124 124 124 124 124 124 124 123 124 124 124 124 124 —
## p-value 0.346572 0.772082 0.003370 0.002500 0.523930 0.145667 0.473424 0.196817 0.715364 0.274368 0.012602 0.000852 < .000001 < .000001 —
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Asian participants
GEE Model for Speeded Trust Task
## (Intercept) fluidity race_multi race_black
## 3.0902400 -0.0267396 -0.0970615 -0.1643504
## fluidity:race_multi fluidity:race_black
## -0.0132841 0.0254801
term | estimate | std.error | statistic | p.value | NA |
---|---|---|---|---|---|
(Intercept) | 3.0902 | 0.0855 | 36.1438 | 0.2349 | 13.1563 |
fluidity | -0.0267 | 0.0193 | -1.3875 | 0.0558 | -0.4796 |
race_multi | -0.0971 | 0.1212 | -0.8011 | 0.1915 | -0.5070 |
race_black | -0.1644 | 0.1213 | -1.3551 | 0.3236 | -0.5078 |
fluidity:race_multi | -0.0133 | 0.0273 | -0.4867 | 0.0447 | -0.2974 |
fluidity:race_black | 0.0255 | 0.0273 | 0.9325 | 0.0749 | 0.3400 |
## Estimate Naive S.E. Naive z Robust S.E. Robust z
## (Intercept) 3.0902400 0.0854986 36.143752 0.2348861 13.156334
## fluidity -0.0267396 0.0192711 -1.387549 0.0557559 -0.479583
## race_multi -0.0970615 0.1211550 -0.801135 0.1914575 -0.506961
## race_black -0.1643504 0.1212812 -1.355119 0.3236392 -0.507820
## fluidity:race_multi -0.0132841 0.0272965 -0.486660 0.0446665 -0.297407
## fluidity:race_black 0.0254801 0.0273259 0.932451 0.0749437 0.339990
## (Intercept)
## 0.00000000000000000000000000000000000000156497
## fluidity
## 0.63152393315283306129970242182025685906410217
## race_multi
## 0.61218205963589455986806342480122111737728119
## race_black
## 0.61157961400911942106972674082498997449874878
## fluidity:race_multi
## 0.76615561406480958694942273723427206277847290
## fluidity:race_black
## 0.73386429946117281986062153009697794914245605
Pearson correlation for trust, feeling therm, atma, and authenticty
## [1] "race_ess" "fluidity"
## [3] "trust_therm_multiracial" "trust_therm_black"
## [5] "trust_therm_white" "trust_survey"
## [7] "feel_therm_multiracial" "feel_therm_black"
## [9] "feel_therm_white" "atma"
## [11] "authen" "whitemulti_trust_dif"
## [13] "White" "Multiracial"
## [15] "Black"
##
## CORRELATION MATRIX
##
## Correlation Matrix
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## race_ess fluidity trust_therm_multiracial trust_therm_black trust_therm_white trust_survey feel_therm_multiracial feel_therm_black feel_therm_white atma authen whitemulti_trust_dif White Multiracial Black
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## race_ess Pearson's r —
## df —
## p-value —
##
## fluidity Pearson's r -0.047653 —
## df 102 —
## p-value 0.630970 —
##
## trust_therm_multiracial Pearson's r -0.050869 0.105082 —
## df 102 102 —
## p-value 0.608069 0.288407 —
##
## trust_therm_black Pearson's r -0.160383 0.165218 0.840282 —
## df 102 102 102 —
## p-value 0.103870 0.093723 < .000001 —
##
## trust_therm_white Pearson's r 0.070234 -0.003015 0.582155 0.387191 —
## df 102 102 102 102 —
## p-value 0.478657 0.975767 < .000001 0.000049 —
##
## trust_survey Pearson's r 0.074304 0.160120 0.581107 0.572119 0.287513 —
## df 102 102 102 102 102 —
## p-value 0.453475 0.104446 < .000001 < .000001 0.003083 —
##
## feel_therm_multiracial Pearson's r -0.002166 0.214659 0.688838 0.639772 0.365494 0.488314 —
## df 102 102 102 102 102 102 —
## p-value 0.982590 0.028654 < .000001 < .000001 0.000136 < .000001 —
##
## feel_therm_black Pearson's r -0.058133 0.225942 0.668149 0.751643 0.225482 0.473770 0.834216 —
## df 102 102 102 102 102 102 102 —
## p-value 0.557756 0.021098 < .000001 < .000001 0.021369 < .000001 < .000001 —
##
## feel_therm_white Pearson's r 0.070416 0.083539 0.320000 0.228685 0.580436 0.115642 0.505422 0.386117 —
## df 102 102 102 102 102 102 102 102 —
## p-value 0.477513 0.399163 0.000928 0.019544 < .000001 0.242407 < .000001 0.000052 —
##
## atma Pearson's r -0.058803 -0.187698 0.158942 0.215898 0.097541 0.159239 0.191035 0.216393 0.073108 —
## df 102 102 102 102 102 102 102 102 102 —
## p-value 0.553221 0.056389 0.107056 0.027725 0.324598 0.106392 0.052069 0.027361 0.460798 —
##
## authen Pearson's r 0.018469 0.079922 0.265551 0.289673 0.215747 0.300317 0.214415 0.230163 0.173668 0.294040 —
## df 102 102 102 102 102 102 102 102 102 102 —
## p-value 0.852375 0.419964 0.006440 0.002858 0.027837 0.001952 0.028840 0.018749 0.077885 0.002448 —
##
## whitemulti_trust_dif Pearson's r -0.037658 0.054241 -0.200556 -0.319783 0.159907 -0.368397 -0.306068 -0.346479 0.090038 -0.067415 -0.158636 —
## df 102 102 102 102 102 102 102 102 102 102 102 —
## p-value 0.704297 0.584472 0.041217 0.000936 0.104914 0.000119 0.001579 0.000315 0.363372 0.496527 0.107741 —
##
## White Pearson's r 0.033169 -0.066803 0.128677 0.070227 0.339966 -0.097113 -0.045989 -0.047938 0.196208 0.062724 0.056618 0.392143 —
## df 102 102 102 102 102 102 102 102 102 102 102 102 —
## p-value 0.738179 0.500451 0.192982 0.478701 0.000414 0.326736 0.642956 0.628926 0.045912 0.527022 0.568089 0.000038 —
##
## Multiracial Pearson's r 0.062044 -0.108721 0.281635 0.311797 0.225614 0.178122 0.183276 0.211668 0.131904 0.114474 0.176829 -0.352762 0.722433 —
## df 102 102 102 102 102 102 102 102 102 102 102 102 102 —
## p-value 0.531520 0.271943 0.003776 0.001273 0.021291 0.070445 0.062565 0.031005 0.181961 0.247226 0.072544 0.000240 < .000001 —
##
## Black Pearson's r 0.056440 -0.031430 0.301496 0.404736 0.055989 0.367524 0.258879 0.306030 -0.080820 0.302870 0.302442 -0.360153 0.361503 0.638423 —
## df 102 102 102 102 102 102 102 102 102 102 102 102 102 102 —
## p-value 0.569305 0.751452 0.001869 0.000020 0.572402 0.000124 0.007965 0.001581 0.414742 0.001777 0.001806 0.000173 0.000163 < .000001 —
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Fluidity Should
White participants
GEE Model for Speeded Trust Task
## (Intercept) fluidity_should
## 2.9988506 -0.0151464
## race_multi race_black
## -0.1405444 -0.1380611
## fluidity_should:race_multi fluidity_should:race_black
## 0.0280629 0.0849424
term | estimate | std.error | statistic | p.value | NA |
---|---|---|---|---|---|
(Intercept) | 2.9989 | 0.0654 | 45.8834 | 0.2247 | 13.3467 |
fluidity_should | -0.0151 | 0.0133 | -1.1416 | 0.0456 | -0.3323 |
race_multi | -0.1405 | 0.0924 | -1.5204 | 0.1232 | -1.1410 |
race_black | -0.1381 | 0.0924 | -1.4934 | 0.1937 | -0.7126 |
fluidity_should:race_multi | 0.0281 | 0.0188 | 1.4955 | 0.0252 | 1.1116 |
fluidity_should:race_black | 0.0849 | 0.0188 | 4.5259 | 0.0401 | 2.1187 |
## Estimate Naive S.E. Naive z Robust S.E. Robust z
## (Intercept) 2.9988506 0.0653581 45.88335 0.2246878 13.346743
## fluidity_should -0.0151464 0.0132680 -1.14158 0.0455809 -0.332298
## race_multi -0.1405444 0.0924414 -1.52036 0.1231790 -1.140977
## race_black -0.1380611 0.0924481 -1.49339 0.1937424 -0.712601
## fluidity_should:race_multi 0.0280629 0.0187650 1.49549 0.0252445 1.111645
## fluidity_should:race_black 0.0849424 0.0187680 4.52593 0.0400915 2.118714
## (Intercept)
## 0.000000000000000000000000000000000000000123742
## fluidity_should
## 0.739664433677641008912928555218968540430068970
## race_multi
## 0.253879326186349230098926454957108944654464722
## race_black
## 0.476092417444517579383500560652464628219604492
## fluidity_should:race_multi
## 0.266290659117022598945112576984683983027935028
## fluidity_should:race_black
## 0.034114674348592187447248846865477389656007290
Pearson correlation for trust, feeling therm, atma, and authenticty
## [1] "race_ess" "fluidity_should"
## [3] "trust_therm_multiracial" "trust_therm_black"
## [5] "trust_therm_white" "trust_survey"
## [7] "feel_therm_multiracial" "feel_therm_black"
## [9] "feel_therm_white" "atma"
## [11] "authen" "whitemulti_trust_dif"
## [13] "White" "Multiracial"
## [15] "Black"
##
## CORRELATION MATRIX
##
## Correlation Matrix
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## race_ess fluidity_should trust_therm_multiracial trust_therm_black trust_therm_white trust_survey feel_therm_multiracial feel_therm_black feel_therm_white atma authen whitemulti_trust_dif White Multiracial Black
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## race_ess Pearson's r —
## df —
## p-value —
##
## fluidity_should Pearson's r -0.203465 —
## df 124 —
## p-value 0.022308 —
##
## trust_therm_multiracial Pearson's r 0.071804 0.109527 —
## df 124 124 —
## p-value 0.424291 0.222138 —
##
## trust_therm_black Pearson's r 0.052926 0.121452 0.928517 —
## df 124 124 124 —
## p-value 0.556142 0.175504 < .000001 —
##
## trust_therm_white Pearson's r 0.032490 -0.077102 0.725720 0.678889 —
## df 124 124 124 124 —
## p-value 0.717981 0.390827 < .000001 < .000001 —
##
## trust_survey Pearson's r 0.056400 0.182628 0.265421 0.312712 0.135040 —
## df 124 124 124 124 124 —
## p-value 0.530479 0.040676 0.002667 0.000364 0.131649 —
##
## feel_therm_multiracial Pearson's r 0.124000 0.185760 0.550884 0.504880 0.350299 0.375184 —
## df 124 124 124 124 124 124 —
## p-value 0.166551 0.037294 < .000001 < .000001 0.000058 0.000015 —
##
## feel_therm_black Pearson's r 0.145482 0.164177 0.616282 0.622130 0.431740 0.345020 0.854440 —
## df 124 124 124 124 124 124 124 —
## p-value 0.104074 0.066209 < .000001 < .000001 < .000001 0.000076 < .000001 —
##
## feel_therm_white Pearson's r 0.166641 0.115144 0.466953 0.413571 0.495416 0.313951 0.774831 0.676444 —
## df 123 123 123 123 123 123 123 123 —
## p-value 0.063256 0.201014 < .000001 0.000002 < .000001 0.000363 < .000001 < .000001 —
##
## atma Pearson's r 0.001085 -0.126427 0.112446 0.139617 0.093503 0.243322 0.219093 0.253000 0.221969 —
## df 124 124 124 124 124 124 124 124 123 —
## p-value 0.990380 0.158345 0.209986 0.118944 0.297693 0.006043 0.013708 0.004260 0.012851 —
##
## authen Pearson's r -0.086408 0.201936 0.278317 0.302624 0.112794 0.440923 0.289697 0.233963 0.184509 0.444390 —
## df 124 124 124 124 124 124 124 124 123 124 —
## p-value 0.336019 0.023357 0.001602 0.000573 0.208570 < .000001 0.001001 0.008370 0.039411 < .000001 —
##
## whitemulti_trust_dif Pearson's r -0.009522 -0.088217 -0.054158 -0.092074 0.130378 -0.085131 -0.094624 -0.095560 0.031214 0.000572 -0.027690 —
## df 124 124 124 124 124 124 124 124 123 124 124 —
## p-value 0.915722 0.325961 0.546973 0.305169 0.145636 0.343238 0.291911 0.287147 0.729676 0.994929 0.758251 —
##
## White Pearson's r -0.113795 -0.032319 0.240592 0.195180 0.318320 0.050998 0.010358 0.000647 0.121398 0.065059 0.210614 0.419588 —
## df 124 124 124 124 124 124 124 124 123 124 124 124 —
## p-value 0.204535 0.719400 0.006654 0.028512 0.000281 0.570633 0.908352 0.994263 0.177456 0.469208 0.017924 0.000001 —
##
## Multiracial Pearson's r -0.113693 0.029208 0.293804 0.272968 0.243427 0.115245 0.079024 0.069409 0.106294 0.068504 0.243013 -0.274709 0.757528 —
## df 124 124 124 124 124 124 124 124 123 124 124 124 124 —
## p-value 0.204943 0.745438 0.000841 0.001985 0.006020 0.198785 0.379089 0.439947 0.238074 0.445947 0.006109 0.001852 < .000001 —
##
## Black Pearson's r -0.084546 0.151525 0.259290 0.267095 0.057300 0.130368 0.064444 0.115749 0.032938 0.098120 0.221694 -0.293486 0.530366 0.772875 —
## df 124 124 124 124 124 124 124 124 123 124 124 124 124 124 —
## p-value 0.346572 0.090322 0.003370 0.002500 0.523930 0.145667 0.473424 0.196817 0.715364 0.274368 0.012602 0.000852 < .000001 < .000001 —
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Asian participants
GEE Model for Speeded Trust Task
## (Intercept) fluidity_should
## 3.0704081 -0.0229259
## race_multi race_black
## -0.4252518 -0.4408554
## fluidity_should:race_multi fluidity_should:race_black
## 0.0640004 0.0918511
term | estimate | std.error | statistic | p.value | NA |
---|---|---|---|---|---|
(Intercept) | 3.0704 | 0.0767 | 40.0516 | 0.2433 | 12.6218 |
fluidity_should | -0.0229 | 0.0178 | -1.2898 | 0.0590 | -0.3885 |
race_multi | -0.4253 | 0.1084 | -3.9221 | 0.1608 | -2.6449 |
race_black | -0.4409 | 0.1086 | -4.0612 | 0.2493 | -1.7682 |
fluidity_should:race_multi | 0.0640 | 0.0251 | 2.5461 | 0.0378 | 1.6919 |
fluidity_should:race_black | 0.0919 | 0.0252 | 3.6492 | 0.0581 | 1.5821 |
## Estimate Naive S.E. Naive z Robust S.E. Robust z
## (Intercept) 3.0704081 0.0766613 40.05162 0.2432627 12.621781
## fluidity_should -0.0229259 0.0177746 -1.28982 0.0590073 -0.388526
## race_multi -0.4252518 0.1084258 -3.92205 0.1607846 -2.644855
## race_black -0.4408554 0.1085517 -4.06125 0.2493258 -1.768190
## fluidity_should:race_multi 0.0640004 0.0251365 2.54612 0.0378278 1.691889
## fluidity_should:race_black 0.0918511 0.0251700 3.64924 0.0580561 1.582111
## (Intercept)
## 0.00000000000000000000000000000000000160158
## fluidity_should
## 0.69762645495660846606256200175266712903976
## race_multi
## 0.00817260178256246951067343076147153624333
## race_black
## 0.07702919166297308994906245516176568344235
## fluidity_should:race_multi
## 0.09066711377869396404349799922783859074116
## fluidity_should:race_black
## 0.11362423141320576736035263820667751133442
Pearson correlation for trust, feeling therm, atma, and authenticty
## [1] "race_ess" "fluidity_should"
## [3] "trust_therm_multiracial" "trust_therm_black"
## [5] "trust_therm_white" "trust_survey"
## [7] "feel_therm_multiracial" "feel_therm_black"
## [9] "feel_therm_white" "atma"
## [11] "authen" "whitemulti_trust_dif"
## [13] "White" "Multiracial"
## [15] "Black"
##
## CORRELATION MATRIX
##
## Correlation Matrix
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## race_ess fluidity_should trust_therm_multiracial trust_therm_black trust_therm_white trust_survey feel_therm_multiracial feel_therm_black feel_therm_white atma authen whitemulti_trust_dif White Multiracial Black
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## race_ess Pearson's r —
## df —
## p-value —
##
## fluidity_should Pearson's r -0.204568 —
## df 102 —
## p-value 0.037246 —
##
## trust_therm_multiracial Pearson's r -0.050869 0.180006 —
## df 102 102 —
## p-value 0.608069 0.067477 —
##
## trust_therm_black Pearson's r -0.160383 0.229833 0.840282 —
## df 102 102 102 —
## p-value 0.103870 0.018924 < .000001 —
##
## trust_therm_white Pearson's r 0.070234 0.046145 0.582155 0.387191 —
## df 102 102 102 102 —
## p-value 0.478657 0.641828 < .000001 0.000049 —
##
## trust_survey Pearson's r 0.074304 0.268916 0.581107 0.572119 0.287513 —
## df 102 102 102 102 102 —
## p-value 0.453475 0.005775 < .000001 < .000001 0.003083 —
##
## feel_therm_multiracial Pearson's r -0.002166 0.245046 0.688838 0.639772 0.365494 0.488314 —
## df 102 102 102 102 102 102 —
## p-value 0.982590 0.012171 < .000001 < .000001 0.000136 < .000001 —
##
## feel_therm_black Pearson's r -0.058133 0.245476 0.668149 0.751643 0.225482 0.473770 0.834216 —
## df 102 102 102 102 102 102 102 —
## p-value 0.557756 0.012016 < .000001 < .000001 0.021369 < .000001 < .000001 —
##
## feel_therm_white Pearson's r 0.070416 0.119366 0.320000 0.228685 0.580436 0.115642 0.505422 0.386117 —
## df 102 102 102 102 102 102 102 102 —
## p-value 0.477513 0.227469 0.000928 0.019544 < .000001 0.242407 < .000001 0.000052 —
##
## atma Pearson's r -0.058803 -0.132166 0.158942 0.215898 0.097541 0.159239 0.191035 0.216393 0.073108 —
## df 102 102 102 102 102 102 102 102 102 —
## p-value 0.553221 0.181086 0.107056 0.027725 0.324598 0.106392 0.052069 0.027361 0.460798 —
##
## authen Pearson's r 0.018469 0.139011 0.265551 0.289673 0.215747 0.300317 0.214415 0.230163 0.173668 0.294040 —
## df 102 102 102 102 102 102 102 102 102 102 —
## p-value 0.852375 0.159325 0.006440 0.002858 0.027837 0.001952 0.028840 0.018749 0.077885 0.002448 —
##
## whitemulti_trust_dif Pearson's r -0.037658 -0.149637 -0.200556 -0.319783 0.159907 -0.368397 -0.306068 -0.346479 0.090038 -0.067415 -0.158636 —
## df 102 102 102 102 102 102 102 102 102 102 102 —
## p-value 0.704297 0.129491 0.041217 0.000936 0.104914 0.000119 0.001579 0.000315 0.363372 0.496527 0.107741 —
##
## White Pearson's r 0.033169 -0.052190 0.128677 0.070227 0.339966 -0.097113 -0.045989 -0.047938 0.196208 0.062724 0.056618 0.392143 —
## df 102 102 102 102 102 102 102 102 102 102 102 102 —
## p-value 0.738179 0.598773 0.192982 0.478701 0.000414 0.326736 0.642956 0.628926 0.045912 0.527022 0.568089 0.000038 —
##
## Multiracial Pearson's r 0.062044 0.059387 0.281635 0.311797 0.225614 0.178122 0.183276 0.211668 0.131904 0.114474 0.176829 -0.352762 0.722433 —
## df 102 102 102 102 102 102 102 102 102 102 102 102 102 —
## p-value 0.531520 0.549282 0.003776 0.001273 0.021291 0.070445 0.062565 0.031005 0.181961 0.247226 0.072544 0.000240 < .000001 —
##
## Black Pearson's r 0.056440 0.106883 0.301496 0.404736 0.055989 0.367524 0.258879 0.306030 -0.080820 0.302870 0.302442 -0.360153 0.361503 0.638423 —
## df 102 102 102 102 102 102 102 102 102 102 102 102 102 102 —
## p-value 0.569305 0.280178 0.001869 0.000020 0.572402 0.000124 0.007965 0.001581 0.414742 0.001777 0.001806 0.000173 0.000163 < .000001 —
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Examining implicit attitudes as a mediator for explicit attitudes
It appears that the white/multiracial trust difference score independently predicts both the trust thermometer and the feeling thermometer ### Trust Survey
## lavaan 0.6.15 ended normally after 20 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 7
##
## Used Total
## Number of observations 296 297
##
## Model Test User Model:
##
## Test statistic 0.000
## Degrees of freedom 0
##
## Model Test Baseline Model:
##
## Test statistic 12.085
## Degrees of freedom 3
## P-value 0.007
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 1.000
## Tucker-Lewis Index (TLI) 1.000
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -510.338
## Loglikelihood unrestricted model (H1) -510.338
##
## Akaike (AIC) 1034.675
## Bayesian (BIC) 1060.508
## Sample-size adjusted Bayesian (SABIC) 1038.309
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.000
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.000
## P-value H_0: RMSEA <= 0.050 NA
## P-value H_0: RMSEA >= 0.080 NA
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.000
##
## Parameter Estimates:
##
## Standard errors Bootstrap
## Number of requested bootstrap draws 500
## Number of successful bootstrap draws 500
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## trust_survey ~
## fluidity (c) 0.067 0.060 1.116 0.265 -0.058 0.192
## whitemulti_trust_dif ~
## fluidity (a) -0.014 0.030 -0.461 0.645 -0.077 0.043
## trust_survey ~
## whtmlt_tr_ (b) -0.389 0.128 -3.034 0.002 -0.644 -0.146
## Std.lv Std.all
##
## 0.067 0.065
##
## -0.014 -0.028
##
## -0.389 -0.185
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## .trust_survey 4.549 0.265 17.166 0.000 4.025 5.132
## .whtmlt_trst_df 0.089 0.132 0.673 0.501 -0.153 0.357
## Std.lv Std.all
## 4.549 5.426
## 0.089 0.223
##
## Variances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## .trust_survey 0.675 0.041 16.319 0.000 0.579 0.750
## .whtmlt_trst_df 0.160 0.018 8.668 0.000 0.127 0.203
## Std.lv Std.all
## 0.675 0.961
## 0.160 0.999
##
## R-Square:
## Estimate
## trust_survey 0.039
## whtmlt_trst_df 0.001
##
## Defined Parameters:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## ab 0.005 0.012 0.446 0.655 -0.021 0.031
## total 0.073 0.062 1.170 0.242 -0.052 0.198
## Std.lv Std.all
## 0.005 0.005
## 0.073 0.070
## [1] lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## <0 rows> (or 0-length row.names)
Trust Thermometer
## lavaan 0.6.15 ended normally after 33 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 7
##
## Used Total
## Number of observations 296 297
##
## Model Test User Model:
##
## Test statistic 0.000
## Degrees of freedom 0
##
## Model Test Baseline Model:
##
## Test statistic 6.753
## Degrees of freedom 3
## P-value 0.080
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 1.000
## Tucker-Lewis Index (TLI) 1.000
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -1429.332
## Loglikelihood unrestricted model (H1) -1429.332
##
## Akaike (AIC) 2872.665
## Bayesian (BIC) 2898.497
## Sample-size adjusted Bayesian (SABIC) 2876.298
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.000
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.000
## P-value H_0: RMSEA <= 0.050 NA
## P-value H_0: RMSEA >= 0.080 NA
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.000
##
## Parameter Estimates:
##
## Standard errors Bootstrap
## Number of requested bootstrap draws 500
## Number of successful bootstrap draws 500
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) ci.lower
## trust_therm_multiracial ~
## fluidity (c) 0.892 1.416 0.630 0.529 -1.962
## whitemulti_trust_dif ~
## fluidity (a) -0.014 0.032 -0.430 0.667 -0.080
## trust_therm_multiracial ~
## whtmlt_tr_ (b) -6.551 2.682 -2.442 0.015 -11.458
## ci.upper Std.lv Std.all
##
## 3.583 0.892 0.039
##
## 0.049 -0.014 -0.028
##
## -1.077 -6.551 -0.141
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## .trst_thrm_mltr 63.896 6.499 9.831 0.000 51.472 77.497
## .whtmlt_trst_df 0.089 0.142 0.626 0.531 -0.186 0.378
## Std.lv Std.all
## 63.896 3.448
## 0.089 0.223
##
## Variances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## .trst_thrm_mltr 335.944 22.724 14.784 0.000 285.718 375.413
## .whtmlt_trst_df 0.160 0.018 8.663 0.000 0.127 0.198
## Std.lv Std.all
## 335.944 0.978
## 0.160 0.999
##
## R-Square:
## Estimate
## trst_thrm_mltr 0.022
## whtmlt_trst_df 0.001
##
## Defined Parameters:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## ab 0.091 0.227 0.403 0.687 -0.392 0.563
## total 0.983 1.414 0.695 0.487 -1.905 3.693
## Std.lv Std.all
## 0.091 0.004
## 0.983 0.043
## [1] lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## <0 rows> (or 0-length row.names)
Attitudes towards multiracial adults
## lavaan 0.6.15 ended normally after 21 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 7
##
## Used Total
## Number of observations 296 297
##
## Model Test User Model:
##
## Test statistic 0.000
## Degrees of freedom 0
##
## Model Test Baseline Model:
##
## Test statistic 16.281
## Degrees of freedom 3
## P-value 0.001
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 1.000
## Tucker-Lewis Index (TLI) 1.000
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -251.651
## Loglikelihood unrestricted model (H1) -251.651
##
## Akaike (AIC) 517.302
## Bayesian (BIC) 543.135
## Sample-size adjusted Bayesian (SABIC) 520.936
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.000
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.000
## P-value H_0: RMSEA <= 0.050 NA
## P-value H_0: RMSEA >= 0.080 NA
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.000
##
## Parameter Estimates:
##
## Standard errors Bootstrap
## Number of requested bootstrap draws 500
## Number of successful bootstrap draws 500
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## atma ~
## fluidity (c) -0.099 0.026 -3.837 0.000 -0.154 -0.054
## whitemulti_trust_dif ~
## fluidity (a) -0.014 0.031 -0.444 0.657 -0.079 0.044
## atma ~
## whtmlt_tr_ (b) 0.029 0.054 0.547 0.584 -0.078 0.140
## Std.lv Std.all
##
## -0.099 -0.226
##
## -0.014 -0.028
##
## 0.029 0.033
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## .atma 3.860 0.120 32.237 0.000 3.643 4.119
## .whtmlt_trst_df 0.089 0.138 0.646 0.518 -0.166 0.384
## Std.lv Std.all
## 3.860 10.954
## 0.089 0.223
##
## Variances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## .atma 0.118 0.009 13.466 0.000 0.099 0.134
## .whtmlt_trst_df 0.160 0.019 8.596 0.000 0.126 0.201
## Std.lv Std.all
## 0.118 0.947
## 0.160 0.999
##
## R-Square:
## Estimate
## atma 0.053
## whtmlt_trst_df 0.001
##
## Defined Parameters:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## ab -0.000 0.002 -0.203 0.839 -0.006 0.004
## total -0.099 0.025 -3.893 0.000 -0.154 -0.054
## Std.lv Std.all
## -0.000 -0.001
## -0.099 -0.227
## [1] lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## <0 rows> (or 0-length row.names)
Feeling thermometer
## lavaan 0.6.15 ended normally after 29 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 7
##
## Used Total
## Number of observations 296 297
##
## Model Test User Model:
##
## Test statistic 0.000
## Degrees of freedom 0
##
## Model Test Baseline Model:
##
## Test statistic 17.621
## Degrees of freedom 3
## P-value 0.001
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 1.000
## Tucker-Lewis Index (TLI) 1.000
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -1419.074
## Loglikelihood unrestricted model (H1) -1419.074
##
## Akaike (AIC) 2852.148
## Bayesian (BIC) 2877.981
## Sample-size adjusted Bayesian (SABIC) 2855.781
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.000
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.000
## P-value H_0: RMSEA <= 0.050 NA
## P-value H_0: RMSEA >= 0.080 NA
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.000
##
## Parameter Estimates:
##
## Standard errors Bootstrap
## Number of requested bootstrap draws 500
## Number of successful bootstrap draws 500
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) ci.lower
## feel_therm_multiracial ~
## fluidity (c) 2.383 1.277 1.867 0.062 -0.178
## whitemulti_trust_dif ~
## fluidity (a) -0.014 0.031 -0.446 0.655 -0.078
## feel_therm_multiracial ~
## whtmlt_tr_ (b) -9.640 2.587 -3.726 0.000 -14.832
## ci.upper Std.lv Std.all
##
## 4.991 2.383 0.106
##
## 0.046 -0.014 -0.028
##
## -4.605 -9.640 -0.211
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## .fl_thrm_mltrcl 59.307 5.771 10.277 0.000 48.011 70.711
## .whtmlt_trst_df 0.089 0.136 0.653 0.514 -0.166 0.371
## Std.lv Std.all
## 59.307 3.253
## 0.089 0.223
##
## Variances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## .fl_thrm_mltrcl 313.447 18.289 17.139 0.000 272.987 344.831
## .whtmlt_trst_df 0.160 0.019 8.582 0.000 0.125 0.196
## Std.lv Std.all
## 313.447 0.943
## 0.160 0.999
##
## R-Square:
## Estimate
## fl_thrm_mltrcl 0.057
## whtmlt_trst_df 0.001
##
## Defined Parameters:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## ab 0.134 0.302 0.445 0.656 -0.491 0.715
## total 2.518 1.329 1.894 0.058 -0.104 5.122
## Std.lv Std.all
## 0.134 0.006
## 2.518 0.111
## [1] lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## <0 rows> (or 0-length row.names)
Authenticity
## lavaan 0.6.15 ended normally after 24 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 7
##
## Used Total
## Number of observations 296 297
##
## Model Test User Model:
##
## Test statistic 0.000
## Degrees of freedom 0
##
## Model Test Baseline Model:
##
## Test statistic 1.276
## Degrees of freedom 3
## P-value 0.735
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 1.000
## Tucker-Lewis Index (TLI) 1.000
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -550.766
## Loglikelihood unrestricted model (H1) -550.766
##
## Akaike (AIC) 1115.532
## Bayesian (BIC) 1141.364
## Sample-size adjusted Bayesian (SABIC) 1119.165
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.000
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.000
## P-value H_0: RMSEA <= 0.050 NA
## P-value H_0: RMSEA >= 0.080 NA
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.000
##
## Parameter Estimates:
##
## Standard errors Bootstrap
## Number of requested bootstrap draws 500
## Number of successful bootstrap draws 500
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## authen ~
## fluidity (c) 0.018 0.072 0.256 0.798 -0.123 0.165
## whitemulti_trust_dif ~
## fluidity (a) -0.014 0.032 -0.438 0.662 -0.074 0.051
## authen ~
## whtmlt_tr_ (b) -0.134 0.147 -0.910 0.363 -0.423 0.168
## Std.lv Std.all
##
## 0.018 0.016
##
## -0.014 -0.028
##
## -0.134 -0.057
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## .authen 5.001 0.325 15.385 0.000 4.342 5.641
## .whtmlt_trst_df 0.089 0.138 0.647 0.518 -0.182 0.358
## Std.lv Std.all
## 5.001 5.300
## 0.089 0.223
##
## Variances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## .authen 0.888 0.060 14.905 0.000 0.763 0.995
## .whtmlt_trst_df 0.160 0.019 8.445 0.000 0.121 0.198
## Std.lv Std.all
## 0.888 0.996
## 0.160 0.999
##
## R-Square:
## Estimate
## authen 0.004
## whtmlt_trst_df 0.001
##
## Defined Parameters:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## ab 0.002 0.006 0.295 0.768 -0.012 0.015
## total 0.020 0.071 0.283 0.777 -0.122 0.164
## Std.lv Std.all
## 0.002 0.002
## 0.020 0.017
## [1] lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## <0 rows> (or 0-length row.names)