Chapter 5 CAMCE’s
Average Marginal Component Effects of turnout level, majority size, and outcome favorability.
if(!require("broom")){install.packages("broom"); library(broom)}
if(!require(descr2)) {devtools::install_github("mikajoh/descr2"); library(descr2)}
if(!require("forcats")){install.packages("forcats"); library(forcats)}
if(!require("ggplot2")){install.packages("ggplot2"); library(ggplot2)}
if(!require("haven")){install.packages("haven"); library(haven)}
if(!require("here")){install.packages("here"); library(here)}
if(!require("kableExtra")){install.packages("kableExtra"); library(kableExtra)}
if(!require("knitr")){install.packages("knitr"); library(knitr)}
if(!require("lmtest")){install.packages("lmtest"); library(lmtest)}
if(!require("sandwich")){install.packages("sandwich"); library(sandwich)}
if(!require("tidyverse")){install.packages("tidyverse"); library(tidyverse)}
knitr::opts_chunk$set(echo = FALSE, knitr.kable.NA = "", cache = FALSE, warning = FALSE, message = FALSE, error = TRUE, echo = FALSE)
#load data
d <- read_sav("Data/EIPS2017-data/eips-wiggle-pooled.sav")
#Function for saving output
ggsave2 <- function(filename, ...) {
for (format in c(".pdf", ".png")) ggsave(filename = paste0("output/", filename, format), ...)
}
## Functions for calculating AMCE's.
source("wiggle-utils.R")
## Theme for ggplot2.
theme_m <- function(...) {
theme(text = element_text(size = 9,
colour = "black"),
axis.text = element_text(size = 7,
colour = "black"),
axis.title = element_text(size = 8,
colour = "black"),
axis.line = element_line(),
axis.ticks = element_line(colour = "black"),
axis.ticks.length = unit(1, "mm"),
plot.margin = unit(c(1, 5, 1, 1), "mm"),
panel.spacing.x = unit(7.5, "mm"),
panel.spacing.y = unit(2.5, "mm"),
panel.background = element_blank(),
panel.grid.major = element_blank(),
strip.background = element_blank(),
strip.text = element_text(size = 7,
face = "bold"),
strip.text.y = element_text(angle = 0, face = "bold.italic"),
legend.background = element_blank(),
legend.key = element_blank(),
legend.position = "bottom",
...)
}
add_labels <- function(amce) {
labels <- data.frame(
treatment = c(
"ref_turnout",
"ref_majoritysize",
"ref_winningside",
"ref_outcome"
),
treatment_label = c(
"Turnout",
"Majority size",
"Winning side",
"Outcome favorability"
),
stringsAsFactors = FALSE
)
amce <- amce[rev(order(amce$value)), ]
amce$value <- paste0("plain('", as.character(amce$value), "')")
amce$value <- factor(amce$value, levels = unique(amce$value))
add_data <- labels[labels$treatment %in% amce$treatment, ]
names(add_data)[2] <- "value"
add_data$value <- gsub("\n", " ", as.character(add_data$value))
add_data$value <- paste0("bold('", add_data$value, "')")
for (var in c("value_order", "estimate", "std_error", "statistic", "p_value")) {
add_data[[var]] <- NA
}
add_data$value_order <- -Inf
if (any(!(names(amce) %in% names(add_data)))) {
for (.c in names(amce)[!(names(amce) %in% names(add_data))]) {
add_data[[.c]] <- amce[[.c]][1]
}
}
if (any(!(names(add_data) %in% names(amce)))) {
for (.c in names(add_data)[!(names(add_data) %in% names(amce))]) {
add_data <- add_data[, -c(which(names(add_data) == .c))]
}
}
amce <- rbind(amce, add_data)
amce <- amce[order(amce$treatment, amce$value_order), ]
return(amce)
}
eips <- eips_raw
eips <- eips %>%
mutate(
ref_turnout = lvls_reorder(factor(ref_turnout),
c(5, 4:1)),
ref_majoritysize = lvls_reorder(factor(ref_majoritysize),
c(4, 3:1)),
ref_winner = lvls_reorder(factor(ref_winner),
c(2, 1, 3)),
ref_outcome = lvls_reorder(factor(ref_outcome),
c(2, 1, 3))
)
## Write prepared data to file.
save(eips, file = "output/eips-wiggle-prepared-data.RData")
## Load the prepared data.
load("output/eips-wiggle-prepared-data.RData")| ref_outcome | Treatment | Value | Estimate | Std.error | t.statistic |
|---|---|---|---|---|---|
| Not shown | Turnout | Not shown | 0.0000000 | 0.0000000 | NA |
| Not shown | Turnout | 85% | 0.0579733 | 0.0187149 | 3.0977034 |
| Not shown | Turnout | 53% | -0.0442623 | 0.0187273 | -2.3635152 |
| Not shown | Turnout | 47% | -0.1292752 | 0.0187232 | -6.9045542 |
| Not shown | Turnout | 35% | -0.2041553 | 0.0188892 | -10.8080587 |
| Favorable outcome | Turnout | Not shown | 0.0000000 | 0.0000000 | NA |
| Favorable outcome | Turnout | 85% | 0.0202834 | 0.0177683 | 1.1415454 |
| Favorable outcome | Turnout | 53% | -0.0636476 | 0.0179427 | -3.5472633 |
| Favorable outcome | Turnout | 47% | -0.1041038 | 0.0179613 | -5.7960031 |
| Favorable outcome | Turnout | 35% | -0.1613754 | 0.0174635 | -9.2407037 |
| Unfavorable outcome | Turnout | Not shown | 0.0000000 | 0.0000000 | NA |
| Unfavorable outcome | Turnout | 85% | 0.0263387 | 0.0219661 | 1.1990643 |
| Unfavorable outcome | Turnout | 53% | -0.0953758 | 0.0218031 | -4.3744226 |
| Unfavorable outcome | Turnout | 47% | -0.1684346 | 0.0219997 | -7.6562171 |
| Unfavorable outcome | Turnout | 35% | -0.2103855 | 0.0217196 | -9.6864474 |
| Not shown | Majority size | Not shown | 0.0000000 | 0.0000000 | NA |
| Not shown | Majority size | 70% | 0.0342749 | 0.0171501 | 1.9985229 |
| Not shown | Majority size | 55% | -0.0335545 | 0.0173061 | -1.9388854 |
| Not shown | Majority size | 51% | -0.0389690 | 0.0164569 | -2.3679381 |
| Favorable outcome | Majority size | Not shown | 0.0000000 | 0.0000000 | NA |
| Favorable outcome | Majority size | 70% | 0.0041500 | 0.0162894 | 0.2547701 |
| Favorable outcome | Majority size | 55% | -0.0545771 | 0.0163406 | -3.3399689 |
| Favorable outcome | Majority size | 51% | -0.0352046 | 0.0152625 | -2.3066125 |
| Unfavorable outcome | Majority size | Not shown | 0.0000000 | 0.0000000 | NA |
| Unfavorable outcome | Majority size | 70% | -0.0114943 | 0.0202411 | -0.5678700 |
| Unfavorable outcome | Majority size | 55% | -0.0336291 | 0.0197602 | -1.7018618 |
| Unfavorable outcome | Majority size | 51% | -0.0573047 | 0.0188676 | -3.0372055 |
##
## Call:
## lm(formula = ref_post ~ ref_turnout + ref_majoritysize + ref_outcome +
## ref_turnout:ref_outcome + ref_outcome:ref_majoritysize, data = eips)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.8963 -0.5204 0.2212 0.3224 0.5535
##
## Coefficients:
## Estimate Std. Error
## (Intercept) 0.752919 0.015929
## ref_turnout85% 0.056294 0.018369
## ref_turnout53% -0.046509 0.018385
## ref_turnout47% -0.130506 0.018376
## ref_turnout35% -0.202145 0.018544
## ref_majoritysize70% 0.031700 0.016541
## ref_majoritysize55% -0.030375 0.016681
## ref_majoritysize51% -0.031870 0.015872
## ref_outcomeFavorable outcome 0.118264 0.023443
## ref_outcomeUnfavorable outcome -0.043441 0.023955
## ref_turnout85%:ref_outcomeFavorable outcome -0.035302 0.026982
## ref_turnout53%:ref_outcomeFavorable outcome -0.017071 0.027134
## ref_turnout47%:ref_outcomeFavorable outcome 0.026833 0.027141
## ref_turnout35%:ref_outcomeFavorable outcome 0.041986 0.026857
## ref_turnout85%:ref_outcomeUnfavorable outcome -0.028851 0.027449
## ref_turnout53%:ref_outcomeUnfavorable outcome -0.047924 0.027344
## ref_turnout47%:ref_outcomeUnfavorable outcome -0.036456 0.027477
## ref_turnout35%:ref_outcomeUnfavorable outcome -0.006962 0.027399
## ref_majoritysize70%:ref_outcomeFavorable outcome -0.027566 0.024374
## ref_majoritysize55%:ref_outcomeFavorable outcome -0.022749 0.024508
## ref_majoritysize51%:ref_outcomeFavorable outcome -0.001571 0.023095
## ref_majoritysize70%:ref_outcomeUnfavorable outcome -0.044503 0.024802
## ref_majoritysize55%:ref_outcomeUnfavorable outcome -0.003977 0.024570
## ref_majoritysize51%:ref_outcomeUnfavorable outcome -0.022033 0.023424
## t value Pr(>|t|)
## (Intercept) 47.267 < 2e-16 ***
## ref_turnout85% 3.065 0.00218 **
## ref_turnout53% -2.530 0.01142 *
## ref_turnout47% -7.102 1.28e-12 ***
## ref_turnout35% -10.901 < 2e-16 ***
## ref_majoritysize70% 1.916 0.05533 .
## ref_majoritysize55% -1.821 0.06863 .
## ref_majoritysize51% -2.008 0.04467 *
## ref_outcomeFavorable outcome 5.045 4.59e-07 ***
## ref_outcomeUnfavorable outcome -1.813 0.06979 .
## ref_turnout85%:ref_outcomeFavorable outcome -1.308 0.19077
## ref_turnout53%:ref_outcomeFavorable outcome -0.629 0.52928
## ref_turnout47%:ref_outcomeFavorable outcome 0.989 0.32285
## ref_turnout35%:ref_outcomeFavorable outcome 1.563 0.11799
## ref_turnout85%:ref_outcomeUnfavorable outcome -1.051 0.29323
## ref_turnout53%:ref_outcomeUnfavorable outcome -1.753 0.07968 .
## ref_turnout47%:ref_outcomeUnfavorable outcome -1.327 0.18460
## ref_turnout35%:ref_outcomeUnfavorable outcome -0.254 0.79942
## ref_majoritysize70%:ref_outcomeFavorable outcome -1.131 0.25809
## ref_majoritysize55%:ref_outcomeFavorable outcome -0.928 0.35329
## ref_majoritysize51%:ref_outcomeFavorable outcome -0.068 0.94576
## ref_majoritysize70%:ref_outcomeUnfavorable outcome -1.794 0.07278 .
## ref_majoritysize55%:ref_outcomeUnfavorable outcome -0.162 0.87143
## ref_majoritysize51%:ref_outcomeUnfavorable outcome -0.941 0.34691
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4481 on 15863 degrees of freedom
## (1518 observations deleted due to missingness)
## Multiple R-squared: 0.06455, Adjusted R-squared: 0.06319
## F-statistic: 47.59 on 23 and 15863 DF, p-value: < 2.2e-16| term | Estimate | Std.error | t.statistic | p.value |
|---|---|---|---|---|
| (Intercept) | 0.7529194 | 0.0159292 | 47.2665087 | 0.0000000 |
| ref_turnout85% | 0.0562941 | 0.0183694 | 3.0645652 | 0.0021835 |
| ref_turnout53% | -0.0465091 | 0.0183850 | -2.5297381 | 0.0114244 |
| ref_turnout47% | -0.1305057 | 0.0183762 | -7.1019052 | 0.0000000 |
| ref_turnout35% | -0.2021451 | 0.0185438 | -10.9009523 | 0.0000000 |
| ref_majoritysize70% | 0.0317001 | 0.0165413 | 1.9164190 | 0.0553297 |
| ref_majoritysize55% | -0.0303754 | 0.0166806 | -1.8209985 | 0.0686259 |
| ref_majoritysize51% | -0.0318703 | 0.0158721 | -2.0079493 | 0.0446656 |
| ref_outcomeFavorable outcome | 0.1182636 | 0.0234434 | 5.0446439 | 0.0000005 |
| ref_outcomeUnfavorable outcome | -0.0434408 | 0.0239554 | -1.8134054 | 0.0697882 |
| ref_turnout85%:ref_outcomeFavorable outcome | -0.0353022 | 0.0269822 | -1.3083481 | 0.1907742 |
| ref_turnout53%:ref_outcomeFavorable outcome | -0.0170709 | 0.0271343 | -0.6291264 | 0.5292754 |
| ref_turnout47%:ref_outcomeFavorable outcome | 0.0268330 | 0.0271413 | 0.9886412 | 0.3228538 |
| ref_turnout35%:ref_outcomeFavorable outcome | 0.0419862 | 0.0268566 | 1.5633474 | 0.1179909 |
| ref_turnout85%:ref_outcomeUnfavorable outcome | -0.0288512 | 0.0274486 | -1.0510993 | 0.2932290 |
| ref_turnout53%:ref_outcomeUnfavorable outcome | -0.0479237 | 0.0273437 | -1.7526378 | 0.0796835 |
| ref_turnout47%:ref_outcomeUnfavorable outcome | -0.0364563 | 0.0274769 | -1.3267965 | 0.1845951 |
| ref_turnout35%:ref_outcomeUnfavorable outcome | -0.0069621 | 0.0273992 | -0.2540999 | 0.7994217 |
| ref_majoritysize70%:ref_outcomeFavorable outcome | -0.0275656 | 0.0243737 | -1.1309565 | 0.2580905 |
| ref_majoritysize55%:ref_outcomeFavorable outcome | -0.0227491 | 0.0245076 | -0.9282445 | 0.3532949 |
| ref_majoritysize51%:ref_outcomeFavorable outcome | -0.0015713 | 0.0230947 | -0.0680369 | 0.9457571 |
| ref_majoritysize70%:ref_outcomeUnfavorable outcome | -0.0445029 | 0.0248024 | -1.7943004 | 0.0727843 |
| ref_majoritysize55%:ref_outcomeUnfavorable outcome | -0.0039766 | 0.0245699 | -0.1618496 | 0.8714264 |
| ref_majoritysize51%:ref_outcomeUnfavorable outcome | -0.0220330 | 0.0234239 | -0.9406202 | 0.3469139 |