MIFT Rutgers Study 2 Data Analysis

Rutgers Study 2 Additional Exploratory Data Analysis

Note: For all analyses, participants who failed one or more manipulation checks, who guessed the hypothesis, or who suspected that they would not be meeting a real person were filtered out

Are there differences by conditions between certainty in race categorization, partner ambiguity & categorization ratings?

Certainty

certainrace = how certain are you of the race of your interaction partner?

Analysis of Variance Table
  Df Sum Sq Mean Sq F value Pr(>F)
miftR2_full$condition 2 0.2502 0.1251 0.07519 0.9276
Residuals 237 394.3 1.664 NA NA
  eta.sq eta.sq.part
miftR2_full$condition 0.0006341 0.0006341

  • miftR2_full$condition:

      diff lwr upr p adj
    FluidBiracial-Control -0.07105 -0.5393 0.3972 0.9318
    FluidBlack-Control -0.004119 -0.4853 0.4771 0.9998
    FluidBlack-FluidBiracial 0.06693 -0.439 0.5728 0.9478

Ambiguity

partnerambig = how racially ambiguous does your interaction partner look?

Analysis of Variance Table
  Df Sum Sq Mean Sq F value Pr(>F)
miftR2_full$condition 2 3.843 1.922 2.387 0.09414
Residuals 237 190.8 0.8051 NA NA
  eta.sq eta.sq.part
miftR2_full$condition 0.01974 0.01974

  • miftR2_full$condition:

      diff lwr upr p adj
    FluidBiracial-Control -0.3021 -0.6282 0.02406 0.07591
    FluidBlack-Control -0.1282 -0.4622 0.2058 0.6377
    FluidBlack-FluidBiracial 0.1739 -0.1791 0.5269 0.4772

Hard to categorize

partnerhardcat = do you think your partner was hard to categorize racially?

Analysis of Variance Table
  Df Sum Sq Mean Sq F value Pr(>F)
miftR2_full$condition 2 0.1977 0.09883 0.3918 0.6763
Residuals 237 59.79 0.2523 NA NA
  eta.sq eta.sq.part
miftR2_full$condition 0.003295 0.003295

  • miftR2_full$condition:

      diff lwr upr p adj
    FluidBiracial-Control 0.01125 -0.1713 0.1938 0.9884
    FluidBlack-Control 0.06748 -0.1195 0.2544 0.6715
    FluidBlack-FluidBiracial 0.05623 -0.1414 0.2538 0.7805

Checking to see if removing the participants who signaled guessing the hypothesis or that they would not meet a real person during debriefing alters the main analyses

This section replicates the orginal analyses conducted by Analia.

DVs: anxiety (anxietyM), liking (likingM), creativity (pastacount), essentialism (EssBio, EssSoc), black-white venn (AAWhVenn)

Anxiety

Analysis of Variance Table
  Df Sum Sq Mean Sq F value Pr(>F)
miftR2_full$condition 2 9.856 4.928 6.553 0.001697
Residuals 238 179 0.752 NA NA
  eta.sq eta.sq.part
miftR2_full$condition 0.05219 0.05219

  • miftR2_full$condition:

      diff lwr upr p adj
    FluidBiracial-Control 0.3657 0.05166 0.6797 0.01776
    FluidBlack-Control 0.453 0.1303 0.7758 0.003082
    FluidBlack-FluidBiracial 0.08737 -0.2527 0.4275 0.817

Liking

Analysis of Variance Table
  Df Sum Sq Mean Sq F value Pr(>F)
miftR2_full$condition 2 1.417 0.7086 0.862 0.4236
Residuals 238 195.7 0.8221 NA NA
  eta.sq eta.sq.part
miftR2_full$condition 0.007192 0.007192

  • miftR2_full$condition:

      diff lwr upr p adj
    FluidBiracial-Control -0.00932 -0.3376 0.319 0.9975
    FluidBlack-Control 0.1653 -0.1722 0.5028 0.4812
    FluidBlack-FluidBiracial 0.1746 -0.181 0.5302 0.4794

Creativity

Analysis of Variance Table
  Df Sum Sq Mean Sq F value Pr(>F)
miftR2_full$condition 2 3.012 1.506 0.5513 0.5769
Residuals 240 655.7 2.732 NA NA
  eta.sq eta.sq.part
miftR2_full$condition 0.004573 0.004573

  • miftR2_full$condition:

      diff lwr upr p adj
    FluidBiracial-Control 0.2553 -0.341 0.8516 0.5715
    FluidBlack-Control 0.1812 -0.4314 0.7939 0.7651
    FluidBlack-FluidBiracial -0.07403 -0.7178 0.5697 0.9603

Essentialism

Biological essentialism

Analysis of Variance Table
  Df Sum Sq Mean Sq F value Pr(>F)
miftR2_full$condition 2 3.19 1.595 1.202 0.3025
Residuals 240 318.6 1.327 NA NA
  eta.sq eta.sq.part
miftR2_full$condition 0.009915 0.009915

  • miftR2_full$condition:

      diff lwr upr p adj
    FluidBiracial-Control 0.2732 -0.1424 0.6889 0.2695
    FluidBlack-Control 0.1243 -0.3027 0.5513 0.7716
    FluidBlack-FluidBiracial -0.1489 -0.5976 0.2998 0.714

Social (?) Essentialism

Analysis of Variance Table
  Df Sum Sq Mean Sq F value Pr(>F)
miftR2_full$condition 2 1.557 0.7786 0.4014 0.6698
Residuals 240 465.6 1.94 NA NA
  eta.sq eta.sq.part
miftR2_full$condition 0.003334 0.003334

  • miftR2_full$condition:

      diff lwr upr p adj
    FluidBiracial-Control 0.1511 -0.3514 0.6536 0.7583
    FluidBlack-Control -0.04077 -0.557 0.4755 0.9811
    FluidBlack-FluidBiracial -0.1919 -0.7343 0.3506 0.6821

Black-white Venn Diagram

Analysis of Variance Table
  Df Sum Sq Mean Sq F value Pr(>F)
miftR2_full$condition 2 8.983 4.492 1.754 0.1752
Residuals 240 614.5 2.56 NA NA
  eta.sq eta.sq.part
miftR2_full$condition 0.01441 0.01441

  • miftR2_full$condition:

      diff lwr upr p adj
    FluidBiracial-Control 0.4585 -0.1188 1.036 0.1488
    FluidBlack-Control 0.2104 -0.3827 0.8035 0.6806
    FluidBlack-FluidBiracial -0.2481 -0.8712 0.3751 0.6164

Checking to see if there is any interaction with participant race

Participant race: P_raceR (asian (0) vs non-asian (1))

Descriptives by condition and participant race

## 
##  Descriptive statistics by group 
## condition: Control
## P_raceR: 0
##            vars  n mean   sd median trimmed  mad  min  max range  skew kurtosis
## anxietyM      1 43 2.32 0.99   2.17    2.25 1.24 1.00 4.67  3.67  0.41    -0.64
## likingM       2 43 4.26 0.91   4.25    4.29 1.11 1.75 6.00  4.25 -0.37    -0.10
## pastacount    3 43 1.44 1.52   1.00    1.26 1.48 0.00 5.00  5.00  0.73    -0.57
## EssBio        4 43 2.99 1.19   3.00    3.02 1.48 1.00 5.00  4.00 -0.08    -1.16
## EssSoc        5 43 3.34 1.29   3.25    3.31 1.48 1.00 7.00  6.00  0.39    -0.20
## AAWhVenn      6 43 5.35 1.23   5.00    5.26 1.48 4.00 8.00  4.00  0.53    -0.96
##              se
## anxietyM   0.15
## likingM    0.14
## pastacount 0.23
## EssBio     0.18
## EssSoc     0.20
## AAWhVenn   0.19
## ------------------------------------------------------------ 
## condition: FluidBiracial
## P_raceR: 0
##            vars  n mean   sd median trimmed  mad min  max range  skew kurtosis
## anxietyM      1 45 2.96 0.76   3.17    3.02 0.49   1 4.33  3.33 -0.75     0.39
## likingM       2 45 4.27 0.97   4.25    4.37 0.74   1 5.75  4.75 -1.15     1.63
## pastacount    3 46 1.72 1.54   1.50    1.61 2.22   0 5.00  5.00  0.54    -0.91
## EssBio        4 46 3.33 1.23   3.33    3.32 1.48   1 5.67  4.67  0.08    -0.89
## EssSoc        5 46 3.84 1.43   3.50    3.76 1.48   1 7.00  6.00  0.42    -0.65
## AAWhVenn      6 46 5.67 1.35   5.50    5.61 2.22   4 8.00  4.00  0.33    -1.13
##              se
## anxietyM   0.11
## likingM    0.14
## pastacount 0.23
## EssBio     0.18
## EssSoc     0.21
## AAWhVenn   0.20
## ------------------------------------------------------------ 
## condition: FluidBlack
## P_raceR: 0
##            vars  n mean   sd median trimmed  mad  min  max range  skew kurtosis
## anxietyM      1 38 2.97 0.83   2.83    2.97 0.74 1.00 5.00  4.00  0.06    -0.13
## likingM       2 38 4.45 0.88   4.50    4.54 0.74 1.75 6.00  4.25 -1.04     1.19
## pastacount    3 38 1.71 1.66   1.00    1.59 1.48 0.00 5.00  5.00  0.49    -1.18
## EssBio        4 38 2.99 1.18   2.67    2.93 1.24 1.33 5.67  4.33  0.48    -0.78
## EssSoc        5 38 3.60 1.26   3.50    3.55 1.48 1.25 6.00  4.75  0.29    -0.92
## AAWhVenn      6 38 5.39 1.50   5.00    5.22 1.48 4.00 9.00  5.00  0.97    -0.15
##              se
## anxietyM   0.14
## likingM    0.14
## pastacount 0.27
## EssBio     0.19
## EssSoc     0.21
## AAWhVenn   0.24
## ------------------------------------------------------------ 
## condition: Control
## P_raceR: 1
##            vars  n mean   sd median trimmed  mad min   max range  skew kurtosis
## anxietyM      1 53 2.55 0.76   2.33    2.55 0.74   1  4.17  3.17  0.13    -0.58
## likingM       2 53 4.33 1.02   4.50    4.37 1.11   2  6.00  4.00 -0.34    -0.80
## pastacount    3 53 1.94 1.73   1.00    1.81 1.48   0  5.00  5.00  0.53    -1.08
## EssBio        4 53 2.66 1.06   2.67    2.62 0.99   1  5.00  4.00  0.25    -0.97
## EssSoc        5 53 3.76 1.47   3.75    3.68 1.11   1  7.00  6.00  0.40    -0.49
## AAWhVenn      6 53 5.60 1.71   5.00    5.37 1.48   4 10.00  6.00  0.88    -0.31
##              se
## anxietyM   0.10
## likingM    0.14
## pastacount 0.24
## EssBio     0.14
## EssSoc     0.20
## AAWhVenn   0.24
## ------------------------------------------------------------ 
## condition: FluidBiracial
## P_raceR: 1
##            vars  n mean   sd median trimmed  mad min   max range  skew kurtosis
## anxietyM      1 31 2.60 0.93   2.50    2.61 1.24   1  4.00  3.00 -0.05    -1.58
## likingM       2 31 4.32 0.66   4.50    4.35 0.74   3  5.50  2.50 -0.32    -0.73
## pastacount    3 31 2.35 1.82   2.00    2.32 2.97   0  5.00  5.00  0.07    -1.48
## EssBio        4 31 2.71 1.01   2.33    2.65 0.99   1  5.67  4.67  0.71     0.64
## EssSoc        5 31 3.56 1.46   3.50    3.42 1.48   1  7.00  6.00  0.66     0.06
## AAWhVenn      6 31 6.35 1.87   7.00    6.24 1.48   4 10.00  6.00  0.21    -1.06
##              se
## anxietyM   0.17
## likingM    0.12
## pastacount 0.33
## EssBio     0.18
## EssSoc     0.26
## AAWhVenn   0.34
## ------------------------------------------------------------ 
## condition: FluidBlack
## P_raceR: 1
##            vars  n mean   sd median trimmed  mad  min   max range  skew
## anxietyM      1 31 2.82 0.94   2.67    2.83 0.74 1.00  4.50   3.5 -0.01
## likingM       2 31 4.49 0.88   4.50    4.44 1.11 3.00  6.50   3.5  0.40
## pastacount    3 31 2.16 1.61   2.00    2.08 1.48 0.00  5.00   5.0  0.30
## EssBio        4 31 2.81 1.13   2.67    2.79 0.99 1.00  5.00   4.0  0.23
## EssSoc        5 31 3.49 1.42   3.50    3.43 1.48 1.25  6.75   5.5  0.30
## AAWhVenn      6 31 6.10 1.90   6.00    5.88 1.48 4.00 10.00   6.0  0.71
##            kurtosis   se
## anxietyM      -0.68 0.17
## likingM       -0.53 0.16
## pastacount    -0.98 0.29
## EssBio        -0.97 0.20
## EssSoc        -0.73 0.26
## AAWhVenn      -0.65 0.34

Anxiety

Analysis of Variance Table (continued below)
  Df Sum Sq Mean Sq
miftR2_full$condition 2 9.856 4.928
miftR2_full$P_raceR 1 0.2559 0.2559
miftR2_full\(condition:miftR2_full\)P_raceR 2 3.841 1.921
Residuals 235 174.9 0.7442
  F value Pr(>F)
miftR2_full$condition 6.622 0.001593
miftR2_full$P_raceR 0.3439 0.5582
miftR2_full\(condition:miftR2_full\)P_raceR 2.581 0.07786
Residuals NA NA
  eta.sq eta.sq.part
miftR2_full$condition 0.04961 0.05084
miftR2_full$P_raceR 0.001355 0.001461
miftR2_full\(condition:miftR2_full\)P_raceR 0.02034 0.02149

Liking

Analysis of Variance Table (continued below)
  Df Sum Sq Mean Sq
miftR2_full$condition 2 1.417 0.7086
miftR2_full$P_raceR 1 0.1982 0.1982
miftR2_full\(condition:miftR2_full\)P_raceR 2 0.009693 0.004846
Residuals 235 195.4 0.8317
  F value Pr(>F)
miftR2_full$condition 0.8521 0.4279
miftR2_full$P_raceR 0.2384 0.6258
miftR2_full\(condition:miftR2_full\)P_raceR 0.005827 0.9942
Residuals NA NA
  eta.sq eta.sq.part
miftR2_full$condition 0.007357 0.007364
miftR2_full$P_raceR 0.001006 0.001013
miftR2_full\(condition:miftR2_full\)P_raceR 0.00004918 0.00004959

Creativity

Analysis of Variance Table (continued below)
  Df Sum Sq Mean Sq
miftR2_full$condition 2 3.105 1.553
miftR2_full$P_raceR 1 16.63 16.63
miftR2_full\(condition:miftR2_full\)P_raceR 2 0.3402 0.1701
Residuals 236 637.9 2.703
  F value Pr(>F)
miftR2_full$condition 0.5745 0.5638
miftR2_full$P_raceR 6.151 0.01383
miftR2_full\(condition:miftR2_full\)P_raceR 0.06293 0.939
Residuals NA NA

Essentialism

Biological essentialism

Analysis of Variance Table (continued below)
  Df Sum Sq Mean Sq
miftR2_full$condition 2 3.215 1.607
miftR2_full$P_raceR 1 8.596 8.596
miftR2_full\(condition:miftR2_full\)P_raceR 2 1.805 0.9026
Residuals 236 305.1 1.293
  F value Pr(>F)
miftR2_full$condition 1.243 0.2903
miftR2_full$P_raceR 6.649 0.01053
miftR2_full\(condition:miftR2_full\)P_raceR 0.6981 0.4985
Residuals NA NA

Social (?) Essentialism

Analysis of Variance Table (continued below)
  Df Sum Sq Mean Sq
miftR2_full$condition 2 1.37 0.6852
miftR2_full$P_raceR 1 0.1386 0.1386
miftR2_full\(condition:miftR2_full\)P_raceR 2 5.629 2.815
Residuals 236 458.1 1.941
  F value Pr(>F)
miftR2_full$condition 0.353 0.703
miftR2_full$P_raceR 0.07143 0.7895
miftR2_full\(condition:miftR2_full\)P_raceR 1.45 0.2366
Residuals NA NA

Black-white Venn Diagram

Analysis of Variance Table (continued below)
  Df Sum Sq Mean Sq
miftR2_full$condition 2 8.995 4.497
miftR2_full$P_raceR 1 15.83 15.83
miftR2_full\(condition:miftR2_full\)P_raceR 2 2.713 1.356
Residuals 236 595.4 2.523
  F value Pr(>F)
miftR2_full$condition 1.782 0.1705
miftR2_full$P_raceR 6.275 0.01292
miftR2_full\(condition:miftR2_full\)P_raceR 0.5376 0.5849
Residuals NA NA

Checking to see if there is any moderation by SDO

Anxiety

Estimates for the sdo moderation model
term estimate std.error statistic p.value
(Intercept) 2.5970 0.1607 16.1623 0.0000
condition1 -0.1506 0.1779 -0.8467 0.3980
condition2 0.2506 0.1236 2.0275 0.0437
sdo 0.0523 0.0579 0.9033 0.3673
condition1:sdo 0.1340 0.0665 2.0161 0.0449
condition2:sdo -0.0619 0.0434 -1.4274 0.1548
Summary for the sdo moderation model
r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC deviance df.residual nobs
0.0808 0.0613 0.8594 4.1322 0.0013 5 -302.416 618.833 643.226 173.573 235 241

Liking

Estimates for the sdo moderation model
term estimate std.error statistic p.value
(Intercept) 4.5135 0.1702 26.5194 0.0000
condition1 0.0527 0.1884 0.2798 0.7799
condition2 0.0941 0.1309 0.7185 0.4732
sdo -0.0611 0.0613 -0.9951 0.3207
condition1:sdo -0.0230 0.0704 -0.3268 0.7441
condition2:sdo -0.0120 0.0459 -0.2602 0.7949
Summary for the sdo moderation model
r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC deviance df.residual nobs
0.0118 -0.0092 0.9103 0.562 0.729 5 -316.282 646.564 670.958 194.741 235 241

Creativity

Estimates for the sdo moderation model
term estimate std.error statistic p.value
(Intercept) 1.8427 0.3074 5.9941 0.0000
condition1 0.4282 0.3436 1.2465 0.2138
condition2 0.0053 0.2349 0.0226 0.9820
sdo 0.0083 0.1111 0.0746 0.9406
condition1:sdo -0.1209 0.1284 -0.9418 0.3473
condition2:sdo 0.0044 0.0828 0.0528 0.9579
Summary for the sdo moderation model
r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC deviance df.residual nobs
0.0083 -0.0126 1.6601 0.3977 0.8502 5 -464.942 943.883 968.334 653.187 237 243

Essentialism

Biological essentialism

Estimates for the sdo moderation model
term estimate std.error statistic p.value
(Intercept) 2.5797 0.2119 12.1727 0.0000
condition1 -0.0531 0.2368 -0.2243 0.8227
condition2 0.1529 0.1619 0.9442 0.3461
sdo 0.1448 0.0766 1.8900 0.0600
condition1:sdo 0.0757 0.0885 0.8560 0.3929
condition2:sdo -0.0636 0.0571 -1.1147 0.2661
Summary for the sdo moderation model
r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC deviance df.residual nobs
0.0353 0.0149 1.1444 1.7345 0.1274 5 -374.541 763.081 787.533 310.388 237 243

Social (?) Essentialism

Estimates for the sdo moderation model
term estimate std.error statistic p.value
(Intercept) 3.9683 0.2563 15.4820 0.0000
condition1 -0.0714 0.2864 -0.2494 0.8033
condition2 -0.3051 0.1958 -1.5580 0.1206
sdo -0.1464 0.0927 -1.5804 0.1153
condition1:sdo 0.0598 0.1070 0.5584 0.5771
condition2:sdo 0.1050 0.0690 1.5207 0.1297
Summary for the sdo moderation model
r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC deviance df.residual nobs
0.0279 0.0074 1.3841 1.3628 0.2391 5 -420.759 855.518 879.969 454.056 237 243

Black-white Venn Diagram

Estimates for the sdo moderation model
term estimate std.error statistic p.value
(Intercept) 5.9036 0.2969 19.8854 0.0000
condition1 0.4081 0.3318 1.2301 0.2199
condition2 -0.2083 0.2268 -0.9182 0.3594
sdo -0.0793 0.1073 -0.7390 0.4606
condition1:sdo -0.0715 0.1240 -0.5769 0.5645
condition2:sdo 0.0785 0.0800 0.9821 0.3270
Summary for the sdo moderation model
r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC deviance df.residual nobs
0.023 0.0024 1.6032 1.1143 0.3534 5 -456.46 926.92 951.371 609.145 237 243