# Read the data from indices_table.txt
df <- as.data.frame(readRDS("Israel Survey/data/il_pe.RDS"))
wave_var <- "Wave"
wave_order <- c("First", "Second", "Third", "Fourth", "Fifth", "Sixth")
community_var <- "pe_left_center_right"
community_order <- c("left", "center", "right") # Set "center" as the reference level since it is the 'neutral' level.
dimensions_order <- c("Overall", "Cognitive", "Behavioral", "Social")
# Calculate the Political Extremism Gauge Indices
indices_result <- af_gauge_indices(df, pop_var1 = wave_var, comm_var1 = community_var,
threshold_type = "MAD", k_factor = 1.5)
df <- indices_result$df
# Convert data to a more manageable format for analysis
df <- df %>%
mutate(Wave = factor(Wave, levels = wave_order)) %>%
mutate(!!sym(community_var) := factor(!!sym(community_var), levels = community_order)) %>%
mutate(event_occurred = factor(1, levels = c(0, 1))) # used for pairwise regression
# Print Event Table
event_table <- data.frame(
event_name = c("Inland Terror", "Bennet Gov. Fall", "Judicial Reform", "Gallant Dismissal", "Oct. 7th War"),
waves = c("1-2", "2-3", "3-4", "4-5", "5-6"),
type = c("Security", "Political", "Political", "Political", "Security"),
stringsAsFactors = FALSE
)
gt(event_table) %>%
tab_header(
title = md("**Event Table**"),
)
| Event Table |
| event_name |
waves |
type |
| Inland Terror |
1-2 |
Security |
| Bennet Gov. Fall |
2-3 |
Political |
| Judicial Reform |
3-4 |
Political |
| Gallant Dismissal |
4-5 |
Political |
| Oct. 7th War |
5-6 |
Security |
# add event_type and event_result info to df based on the event_table
df <- af_add_event_info(df, wave_var, wave_order, event_table, community_var)
# Create the wave list in the form
wave_list <- list()
for(i in 1:nrow(event_table)) {
wave_range <- as.numeric(unlist(strsplit(event_table$waves[i], "-")))
wave_list[[event_table$event_name[i]]] <- c(wave_order[wave_range[1]],
wave_order[wave_range[2]])
}
# Create demographics regression formula part
demographics <- c("gender", "age_group") # , "education"
d_fmla <- paste(demographics, collapse = "+")
# Set display names for regression results
display_names <- list(
"Wave" = "Wave",
"post_event1" = "Inland Terror",
"post_event2" = "Bennet Gov. Fall",
"post_event3" = "Judicial Reform",
"post_event4" = "Gallant Dismissal",
"post_event5" = "Oct. 7th War",
"immediate_event1" = "Inland Terror",
"immediate_event2" = "Bennet Gov. Fall",
"immediate_event3" = "Judicial Reform",
"immediate_event4" = "Gallant Dismissal",
"immediate_event5" = "Oct. 7th War",
"pe_left_center_right" = "Political Orientation",
"event_occurred" = "Event Occured",
"event_type" = "Event Type",
"gender" = "Gender",
"age_group" = "Age Group",
"education" = "Education"
)
coef_names <- c(
"event_occurred1" = "Event Occurred",
"pe_left_center_rightcenter" = "Political Orientation[center]",
"pe_left_center_rightright" = "Political Orientation[right]",
"event_occurred1:pe_left_center_rightcenter" = "Event Occurred : Political Orientation[center]",
"event_occurred1:pe_left_center_rightright" = "Event Occurred : Political Orientation[right]"
)
Dimensions
# Create Panel Dataset
df1 <- df$respondent_id[df$Wave == "Third"]
df2 <- df$respondent_id[df$Wave == "Fourth"]
panel_respondents <- intersect(df1, df2)
panel_df <- df %>%
filter(Wave %in% c("Third", "Fourth")) %>%
filter(respondent_id %in% panel_respondents) %>%
mutate(event_occurred = factor(case_when(
Wave == "Third" ~ 0,
Wave == "Fourth" ~ 1
), levels = c(0, 1)))
p_data <- plm::pdata.frame(panel_df, index = c("respondent_id", "event_occurred"))
plm::pdim(p_data)
Balanced Panel: n = 671, T = 2, N = 1342
# The within estimator will automatically drop the main effects of time-invariant variables
# (like pe_left_center_right, gender, age_group) but keeps the interactions event_occurred * pe_left_center_right.
mp1 <- plm(pe_ideology ~ event_occurred * pe_left_center_right + age_group, data = p_data, model = "within")
mp2 <- plm(pe_violence ~ event_occurred * pe_left_center_right + age_group, data = p_data, model = "within")
mp3 <- plm(pe_intolerance ~ event_occurred * pe_left_center_right + age_group, data = p_data, model = "within")
mp4 <- plm(pe_overall ~ event_occurred * pe_left_center_right + age_group, data = p_data, model = "within")
Cognitive
Dimension
formula_str <- paste("pe_ideology ~ event_occurred * pe_left_center_right","+", d_fmla)
models <- af_wave_pair_regression(df, wave_var = wave_var, wave_list = wave_list,
formula_str = formula_str, regression_type = "OLS")
models[[3]] <- mp1 # Override with panel model
coef_table <- af_coef_and_ci_table(models, coef_names)
af_coef_and_ci_plot(coef_table, xpose = TRUE, title = "Cognitive Dimension")
notes <- af_create_regression_notes(df, models = models, display_names = display_names,
show_significance = TRUE, significance_levels = c(0.05, 0.01, 0.001))
cov_labels <- af_cov_names(df, models, display_names)
af_stargazer(models = models, cov_labels = cov_labels, notes = notes,
title = "Cognitive Political Extremism ~ Event Occurred x Political Orientation + Demographics")
Cognitive Political Extremism ~ Event Occurred x Political
Orientation + Demographics
|
|
|
|
Dependent variable:
|
|
|
|
|
|
pe_ideology
|
|
|
OLS
|
panel
|
OLS
|
|
|
|
linear
|
|
|
|
Inland Terror
|
Bennet Gov. Fall
|
Judicial Reform
|
Gallant Dismissal
|
Oct. 7th War
|
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
|
|
|
Event Occured[1]
|
0.041
|
0.459*
|
0.256
|
-0.386
|
0.295
|
|
|
(0.168)
|
(0.194)
|
(0.176)
|
(0.227)
|
(0.211)
|
|
Political Orientation[center]
|
-1.256***
|
-1.320***
|
0.347
|
-1.667***
|
-1.026***
|
|
|
(0.147)
|
(0.131)
|
(0.303)
|
(0.225)
|
(0.158)
|
|
Political Orientation[right]
|
-0.767***
|
-1.222***
|
0.214
|
-1.745***
|
-1.156***
|
|
|
(0.134)
|
(0.121)
|
(0.330)
|
(0.204)
|
(0.147)
|
|
Gender[Female]
|
-0.570***
|
-0.587***
|
|
-0.621***
|
-0.519***
|
|
|
(0.066)
|
(0.068)
|
|
(0.075)
|
(0.070)
|
|
Age Group[31-45]
|
-0.067
|
-0.188*
|
0.123
|
-0.097
|
-0.030
|
|
|
(0.086)
|
(0.089)
|
(1.006)
|
(0.097)
|
(0.095)
|
|
Age Group[46-60]
|
-0.007
|
-0.028
|
1.036
|
0.112
|
0.200*
|
|
|
(0.092)
|
(0.095)
|
(1.299)
|
(0.100)
|
(0.097)
|
|
Age Group[60+]
|
0.302**
|
0.383***
|
|
0.535***
|
0.525***
|
|
|
(0.103)
|
(0.102)
|
|
(0.128)
|
(0.114)
|
|
Event Occured[1] × Political Orientation[center]
|
-0.068
|
-0.360
|
-0.284
|
0.634*
|
-0.240
|
|
|
(0.207)
|
(0.234)
|
(0.211)
|
(0.273)
|
(0.246)
|
|
Event Occured[1] × Political Orientation[right]
|
-0.467*
|
-0.543*
|
-0.233
|
0.570*
|
-0.289
|
|
|
(0.189)
|
(0.214)
|
(0.190)
|
(0.249)
|
(0.229)
|
|
|
|
Observations
|
3,215
|
2,493
|
1,342
|
2,221
|
2,638
|
|
R2
|
0.080
|
0.121
|
0.006
|
0.096
|
0.080
|
|
Adjusted R2
|
0.077
|
0.117
|
-1.007
|
0.092
|
0.077
|
|
|
|
Note: * p < 0.050; ** p < 0.010; *** p < 0.001. The reference
category for Event Occured is ‘0’. The reference category for Political
Orientation is ‘left’. The reference category for Gender is ‘Male’. The
reference category for Age Group is ‘18-30’. Standard errors in
parentheses.
|
Behavioral
Dimension
formula_str <- paste("pe_violence ~ event_occurred * pe_left_center_right","+", d_fmla)
models <- af_wave_pair_regression(df, wave_var = wave_var, wave_list = wave_list,
formula_str = formula_str, regression_type = "OLS")
models[[3]] <- mp2 # Override with panel model
coef_table <- af_coef_and_ci_table(models, coef_names)
af_coef_and_ci_plot(coef_table, xpose = TRUE, title = "Behavioral Dimension")
notes <- af_create_regression_notes(df, models = models, display_names = display_names,
show_significance = TRUE, significance_levels = c(0.05, 0.01, 0.001))
cov_labels <- af_cov_names(df, models, display_names)
af_stargazer(models = models, cov_labels = cov_labels, notes = notes,
title = "Behavioral Political Extremism ~ Event Occurred x Political Orientation + Demographics")
Behavioral Political Extremism ~ Event Occurred x Political
Orientation + Demographics
|
|
|
|
Dependent variable:
|
|
|
|
|
|
pe_violence
|
|
|
OLS
|
panel
|
OLS
|
|
|
|
linear
|
|
|
|
Inland Terror
|
Bennet Gov. Fall
|
Judicial Reform
|
Gallant Dismissal
|
Oct. 7th War
|
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
|
|
|
Event Occured[1]
|
-0.031
|
-0.122
|
0.114
|
0.156
|
0.326**
|
|
|
(0.086)
|
(0.114)
|
(0.102)
|
(0.123)
|
(0.113)
|
|
Political Orientation[center]
|
0.105
|
0.152*
|
0.036
|
0.193
|
0.029
|
|
|
(0.075)
|
(0.077)
|
(0.176)
|
(0.121)
|
(0.085)
|
|
Political Orientation[right]
|
0.165*
|
0.353***
|
-0.027
|
0.092
|
-0.013
|
|
|
(0.069)
|
(0.071)
|
(0.192)
|
(0.110)
|
(0.079)
|
|
Gender[Female]
|
-0.176***
|
-0.192***
|
|
-0.275***
|
-0.269***
|
|
|
(0.034)
|
(0.040)
|
|
(0.040)
|
(0.037)
|
|
Age Group[31-45]
|
-0.131**
|
-0.154**
|
0.512
|
-0.004
|
-0.059
|
|
|
(0.044)
|
(0.052)
|
(0.585)
|
(0.052)
|
(0.051)
|
|
Age Group[46-60]
|
-0.180***
|
-0.256***
|
0.560
|
-0.266***
|
-0.205***
|
|
|
(0.047)
|
(0.056)
|
(0.756)
|
(0.054)
|
(0.052)
|
|
Age Group[60+]
|
-0.283***
|
-0.309***
|
|
-0.193**
|
-0.254***
|
|
|
(0.053)
|
(0.060)
|
|
(0.069)
|
(0.061)
|
|
Event Occured[1] × Political Orientation[center]
|
0.048
|
0.110
|
0.032
|
-0.166
|
-0.205
|
|
|
(0.106)
|
(0.138)
|
(0.122)
|
(0.147)
|
(0.132)
|
|
Event Occured[1] × Political Orientation[right]
|
0.195*
|
0.042
|
-0.192
|
-0.113
|
-0.332**
|
|
|
(0.097)
|
(0.126)
|
(0.111)
|
(0.135)
|
(0.123)
|
|
|
|
Observations
|
3,215
|
2,493
|
1,342
|
2,221
|
2,638
|
|
R2
|
0.034
|
0.043
|
0.019
|
0.039
|
0.033
|
|
Adjusted R2
|
0.031
|
0.040
|
-0.981
|
0.035
|
0.030
|
|
|
|
Note: * p < 0.050; ** p < 0.010; *** p < 0.001. The reference
category for Event Occured is ‘0’. The reference category for Political
Orientation is ‘left’. The reference category for Gender is ‘Male’. The
reference category for Age Group is ‘18-30’. Standard errors in
parentheses.
|
Social Dimension
formula_str <- paste("pe_intolerance ~ event_occurred * pe_left_center_right","+", d_fmla)
models <- af_wave_pair_regression(df, wave_var = wave_var, wave_list = wave_list,
formula_str = formula_str, regression_type = "OLS")
models[[3]] <- mp3 # Override with panel model
coef_table <- af_coef_and_ci_table(models, coef_names)
af_coef_and_ci_plot(coef_table, xpose = TRUE, title = "Social Dimension")
notes <- af_create_regression_notes(df, models = models, display_names = display_names,
show_significance = TRUE, significance_levels = c(0.05, 0.01, 0.001))
cov_labels <- af_cov_names(df, models, display_names)
af_stargazer(models = models, cov_labels = cov_labels, notes = notes,
title = "Social Political Extremism ~ Event Occurred x Political Orientation + Demographics")
Social Political Extremism ~ Event Occurred x Political
Orientation + Demographics
|
|
|
|
Dependent variable:
|
|
|
|
|
|
pe_intolerance
|
|
|
OLS
|
panel
|
OLS
|
|
|
|
linear
|
|
|
|
Inland Terror
|
Bennet Gov. Fall
|
Judicial Reform
|
Gallant Dismissal
|
Oct. 7th War
|
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
|
|
|
Event Occured[1]
|
-0.118
|
-0.051
|
-0.113
|
0.273
|
-0.005
|
|
|
(0.128)
|
(0.167)
|
(0.167)
|
(0.197)
|
(0.181)
|
|
Political Orientation[center]
|
0.814***
|
0.687***
|
0.062
|
0.939***
|
0.679***
|
|
|
(0.112)
|
(0.113)
|
(0.289)
|
(0.195)
|
(0.135)
|
|
Political Orientation[right]
|
1.559***
|
1.807***
|
-0.101
|
1.738***
|
1.449***
|
|
|
(0.103)
|
(0.104)
|
(0.314)
|
(0.176)
|
(0.126)
|
|
Gender[Female]
|
0.002
|
0.089
|
|
-0.018
|
0.046
|
|
|
(0.050)
|
(0.058)
|
|
(0.065)
|
(0.060)
|
|
Age Group[31-45]
|
0.215**
|
0.186*
|
0.728
|
0.136
|
0.188*
|
|
|
(0.066)
|
(0.077)
|
(0.957)
|
(0.084)
|
(0.081)
|
|
Age Group[46-60]
|
0.337***
|
0.257**
|
2.183
|
0.341***
|
0.310***
|
|
|
(0.070)
|
(0.082)
|
(1.237)
|
(0.086)
|
(0.083)
|
|
Age Group[60+]
|
0.461***
|
0.458***
|
|
0.398***
|
0.386***
|
|
|
(0.079)
|
(0.088)
|
|
(0.111)
|
(0.097)
|
|
Event Occured[1] × Political Orientation[center]
|
-0.121
|
0.241
|
0.038
|
-0.266
|
0.068
|
|
|
(0.158)
|
(0.202)
|
(0.200)
|
(0.237)
|
(0.211)
|
|
Event Occured[1] × Political Orientation[right]
|
0.244
|
-0.135
|
0.063
|
-0.294
|
-0.128
|
|
|
(0.145)
|
(0.185)
|
(0.181)
|
(0.216)
|
(0.196)
|
|
|
|
Observations
|
3,215
|
2,493
|
1,342
|
2,221
|
2,638
|
|
R2
|
0.170
|
0.175
|
0.009
|
0.118
|
0.091
|
|
Adjusted R2
|
0.168
|
0.172
|
-1.001
|
0.115
|
0.087
|
|
|
|
Note: * p < 0.050; ** p < 0.010; *** p < 0.001. The reference
category for Event Occured is ‘0’. The reference category for Political
Orientation is ‘left’. The reference category for Gender is ‘Male’. The
reference category for Age Group is ‘18-30’. Standard errors in
parentheses.
|
overall
formula_str <- paste("pe_overall ~ event_occurred * pe_left_center_right","+", d_fmla)
models <- af_wave_pair_regression(df, wave_var = wave_var, wave_list = wave_list,
formula_str = formula_str, regression_type = "OLS")
models[[3]] <- mp4 # Override with panel model
coef_table <- af_coef_and_ci_table(models, coef_names)
af_coef_and_ci_plot(coef_table, xpose = TRUE, title = "Overall (Combined Dimensions)")
notes <- af_create_regression_notes(df, models = models, display_names = display_names,
show_significance = TRUE, significance_levels = c(0.05, 0.01, 0.001))
cov_labels <- af_cov_names(df, models, display_names)
af_stargazer(models = models, cov_labels = cov_labels, notes = notes,
title = "Overall Political Extremism ~ Event Occurred * Political Orientation + Demographics")
Overall Political Extremism ~ Event Occurred * Political
Orientation + Demographics
|
|
|
|
Dependent variable:
|
|
|
|
|
|
pe_overall
|
|
|
OLS
|
panel
|
OLS
|
|
|
|
linear
|
|
|
|
Inland Terror
|
Bennet Gov. Fall
|
Judicial Reform
|
Gallant Dismissal
|
Oct. 7th War
|
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
|
|
|
Event Occured[1]
|
-0.022
|
0.207
|
0.099
|
-0.064
|
0.227*
|
|
|
(0.087)
|
(0.106)
|
(0.096)
|
(0.121)
|
(0.111)
|
|
Political Orientation[center]
|
-0.191*
|
-0.291***
|
0.129
|
-0.344**
|
-0.196*
|
|
|
(0.076)
|
(0.071)
|
(0.165)
|
(0.120)
|
(0.083)
|
|
Political Orientation[right]
|
0.275***
|
0.205**
|
0.017
|
-0.134
|
0.028
|
|
|
(0.070)
|
(0.066)
|
(0.179)
|
(0.109)
|
(0.077)
|
|
Gender[Female]
|
-0.271***
|
-0.238***
|
|
-0.333***
|
-0.262***
|
|
|
(0.034)
|
(0.037)
|
|
(0.040)
|
(0.037)
|
|
Age Group[31-45]
|
0.046
|
-0.013
|
0.540
|
0.013
|
0.051
|
|
|
(0.045)
|
(0.049)
|
(0.547)
|
(0.052)
|
(0.050)
|
|
Age Group[46-60]
|
0.127**
|
0.057
|
1.342
|
0.113*
|
0.155**
|
|
|
(0.048)
|
(0.052)
|
(0.706)
|
(0.053)
|
(0.051)
|
|
Age Group[60+]
|
0.238***
|
0.255***
|
|
0.316***
|
0.293***
|
|
|
(0.054)
|
(0.056)
|
|
(0.068)
|
(0.060)
|
|
Event Occured[1] × Political Orientation[center]
|
-0.098
|
-0.079
|
-0.089
|
0.141
|
-0.136
|
|
|
(0.108)
|
(0.128)
|
(0.114)
|
(0.146)
|
(0.129)
|
|
Event Occured[1] × Political Orientation[right]
|
-0.074
|
-0.323**
|
-0.135
|
0.150
|
-0.287*
|
|
|
(0.098)
|
(0.117)
|
(0.103)
|
(0.133)
|
(0.120)
|
|
|
|
Observations
|
3,215
|
2,493
|
1,342
|
2,221
|
2,638
|
|
R2
|
0.074
|
0.072
|
0.011
|
0.053
|
0.041
|
|
Adjusted R2
|
0.072
|
0.069
|
-0.997
|
0.050
|
0.038
|
|
|
|
Note: * p < 0.050; ** p < 0.010; *** p < 0.001. The reference
category for Event Occured is ‘0’. The reference category for Political
Orientation is ‘left’. The reference category for Gender is ‘Male’. The
reference category for Age Group is ‘18-30’. Standard errors in
parentheses.
|
Individual Extremism
Level
# Logistic regression with the response variable being a binary indicator of whether the respondent
# is part of the more extremist group (counted in the Extremism Level index).
#
# The model asks: "How do event_occurred, political_orientation, and their interaction affect the odds of i_cel = 1,
# controlling for age_group and accounting for unobserved individual-level characteristics?"
mp1 <- clogit(i_cel ~ event_occurred * pe_left_center_right + age_group + cluster(respondent_id),
data = panel_df, method = "approximate")
mp2 <- clogit(i_bel ~ event_occurred * pe_left_center_right + age_group + cluster(respondent_id),
data = panel_df, method = "approximate")
mp3_no_interaction <- clogit(i_sel ~ event_occurred + pe_left_center_right + age_group + cluster(respondent_id),
data = panel_df, method = "approximate")
mp4 <- clogit(i_oel ~ event_occurred * pe_left_center_right + age_group + cluster(respondent_id),
data = panel_df, method = "approximate")
Cognitive
Dimension
formula_str <- paste("i_cel ~ event_occurred * pe_left_center_right","+", d_fmla)
models <- af_wave_pair_regression(df, wave_var = wave_var, wave_list = wave_list,
formula_str = formula_str, regression_type = "Logit")
models[[3]] <- mp1 # Override with panel model
coef_table <- af_coef_and_ci_table(models, coef_names)
af_coef_and_ci_plot(coef_table, xpose = TRUE, title = "Cognitive Dimension",
exp_ctrl = c(TRUE, TRUE, TRUE, TRUE, TRUE))
notes <- af_create_regression_notes(df, models = models, display_names = display_names, is_exp = TRUE,
show_significance = TRUE, significance_levels = c(0.05, 0.01, 0.001))
cov_labels <- af_cov_names(df, models, display_names)
af_stargazer(models = models, cov_labels = cov_labels, coef_exp = TRUE, notes = notes,
title = "Individual Extremist ~ Event Occurred x Political Orientation + Demographics")
Individual Extremist ~ Event Occurred x Political Orientation +
Demographics
|
|
|
|
Dependent variable:
|
|
|
|
|
|
i_cel
|
i_cel
|
i_cel
|
|
|
logistic
|
conditional
|
logistic
|
|
|
|
logistic
|
|
|
|
Inland Terror
|
Bennet Gov. Fall
|
Judicial Reform
|
Gallant Dismissal
|
Oct. 7th War
|
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
|
|
|
Event Occured[1]
|
0.969
|
3.125***
|
0.964
|
0.420**
|
1.456
|
|
|
(0.194)
|
(0.246)
|
(0.220)
|
(0.276)
|
(0.247)
|
|
Political Orientation[center]
|
0.277***
|
0.209***
|
0.217***
|
0.208***
|
0.330***
|
|
|
(0.196)
|
(0.208)
|
(0.257)
|
(0.287)
|
(0.208)
|
|
Political Orientation[right]
|
0.526***
|
0.400***
|
0.282***
|
0.138***
|
0.283***
|
|
|
(0.160)
|
(0.166)
|
(0.200)
|
(0.259)
|
(0.191)
|
|
Gender[Female]
|
0.513***
|
0.468***
|
|
0.402***
|
0.521***
|
|
|
(0.094)
|
(0.112)
|
|
(0.119)
|
(0.105)
|
|
Age Group[31-45]
|
0.932
|
0.912
|
0.887
|
0.875
|
1.073
|
|
|
(0.124)
|
(0.151)
|
(0.172)
|
(0.155)
|
(0.150)
|
|
Age Group[46-60]
|
1.107
|
1.196
|
1.256
|
1.112
|
1.292
|
|
|
(0.129)
|
(0.156)
|
(0.173)
|
(0.156)
|
(0.150)
|
|
Age Group[60+]
|
1.323*
|
1.684**
|
1.848***
|
1.808**
|
1.844***
|
|
|
(0.140)
|
(0.160)
|
(0.175)
|
(0.183)
|
(0.163)
|
|
Event Occured[1] × Political Orientation[center]
|
0.765
|
0.453*
|
1.661**
|
1.518
|
1.061
|
|
|
(0.284)
|
(0.353)
|
(0.339)
|
(0.355)
|
(0.306)
|
|
Event Occured[1] × Political Orientation[right]
|
0.751
|
0.307***
|
0.995
|
1.923*
|
0.783
|
|
|
(0.228)
|
(0.286)
|
(0.278)
|
(0.322)
|
(0.285)
|
|
|
|
Observations
|
3,215
|
2,493
|
1,342
|
2,221
|
2,638
|
|
R2
|
|
|
0.069
|
|
|
|
|
|
Note: * p < 0.050; ** p < 0.010; *** p < 0.001. The reference
category for Event Occured is ‘0’. The reference category for Political
Orientation is ‘left’. The reference category for Gender is ‘Male’. The
reference category for Age Group is ‘18-30’. Standard errors in
parentheses. The coefficients of models 1 and 2 and 3 and 4 and 5 are
exponentiated.
|
Behavioral
Dimension
formula_str <- paste("i_bel ~ event_occurred * pe_left_center_right","+", d_fmla)
models <- af_wave_pair_regression(df, wave_var = wave_var, wave_list = wave_list,
formula_str = formula_str, regression_type = "Logit")
models[[3]] <- mp2 # Override with panel model
coef_table <- af_coef_and_ci_table(models, coef_names)
af_coef_and_ci_plot(coef_table, xpose = TRUE, title = "Behavioral Dimension",
exp_ctrl = c(TRUE, TRUE, TRUE, TRUE, TRUE))
notes <- af_create_regression_notes(df, models = models, display_names = display_names, is_exp = TRUE,
show_significance = TRUE, significance_levels = c(0.05, 0.01, 0.001))
cov_labels <- af_cov_names(df, models, display_names)
af_stargazer(models = models, cov_labels = cov_labels, coef_exp = TRUE, notes = notes,
title = "Individual Extremist ~ Event Occurred x Political Orientation + Demographics")
Individual Extremist ~ Event Occurred x Political Orientation +
Demographics
|
|
|
|
Dependent variable:
|
|
|
|
|
|
i_bel
|
i_bel
|
i_bel
|
|
|
logistic
|
conditional
|
logistic
|
|
|
|
logistic
|
|
|
|
Inland Terror
|
Bennet Gov. Fall
|
Judicial Reform
|
Gallant Dismissal
|
Oct. 7th War
|
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
|
|
|
Event Occured[1]
|
0.521**
|
0.810
|
1.557
|
1.343
|
1.289
|
|
|
(0.211)
|
(0.302)
|
(0.344)
|
(0.286)
|
(0.248)
|
|
Political Orientation[center]
|
0.878
|
1.283
|
1.451
|
1.228
|
0.881
|
|
|
(0.171)
|
(0.194)
|
(0.310)
|
(0.284)
|
(0.191)
|
|
Political Orientation[right]
|
1.250
|
2.319***
|
1.824*
|
0.952
|
0.770
|
|
|
(0.154)
|
(0.176)
|
(0.290)
|
(0.259)
|
(0.178)
|
|
Gender[Female]
|
0.699***
|
0.682***
|
|
0.693***
|
0.637***
|
|
|
(0.077)
|
(0.089)
|
|
(0.095)
|
(0.086)
|
|
Age Group[31-45]
|
0.848
|
0.776*
|
0.891
|
0.988
|
0.928
|
|
|
(0.098)
|
(0.114)
|
(0.121)
|
(0.118)
|
(0.113)
|
|
Age Group[46-60]
|
0.695***
|
0.577***
|
0.422***
|
0.575***
|
0.606***
|
|
|
(0.106)
|
(0.126)
|
(0.163)
|
(0.129)
|
(0.121)
|
|
Age Group[60+]
|
0.615***
|
0.670**
|
0.878
|
0.810
|
0.687**
|
|
|
(0.122)
|
(0.134)
|
(0.147)
|
(0.160)
|
(0.139)
|
|
Event Occured[1] × Political Orientation[center]
|
1.461
|
1.571
|
0.769
|
0.718
|
1.181
|
|
|
(0.258)
|
(0.351)
|
(0.394)
|
(0.343)
|
(0.290)
|
|
Event Occured[1] × Political Orientation[right]
|
1.853**
|
1.111
|
0.515*
|
0.816
|
0.735
|
|
|
(0.233)
|
(0.322)
|
(0.366)
|
(0.315)
|
(0.272)
|
|
|
|
Observations
|
3,215
|
2,493
|
1,342
|
2,221
|
2,638
|
|
R2
|
|
|
0.031
|
|
|
|
|
|
Note: * p < 0.050; ** p < 0.010; *** p < 0.001. The reference
category for Event Occured is ‘0’. The reference category for Political
Orientation is ‘left’. The reference category for Gender is ‘Male’. The
reference category for Age Group is ‘18-30’. Standard errors in
parentheses. The coefficients of models 1 and 2 and 3 and 4 and 5 are
exponentiated.
|
Social Dimension
The social dimension of wave 4 does not have any left
politically-oriented people in the extremism tail, i.e., i_sel == 0 for
all respondents. This means we have perfect separation, and the
regression will provide wrong results (inf). To resolve this, the
interaction term was removed from pairs 3 & 4.
model4_data <- df[df$Wave %in% c("Fourth", "Fifth"), ]
model4_data$event_occurred <- ifelse(model4_data$Wave == "Fourth", 0, 1)
formula_no_interaction <- paste("i_sel ~ event_occurred + pe_left_center_right","+", d_fmla)
model4_no_interaction <- glm(formula_no_interaction, data = model4_data, family = binomial(link = "logit"))
formula_str <- paste("i_sel ~ event_occurred * pe_left_center_right","+", d_fmla)
models <- af_wave_pair_regression(df, wave_var = wave_var, wave_list = wave_list,
formula_str = formula_str, regression_type = "Logit")
models[[3]] <- mp3_no_interaction # Override with panel no-interaction model
models[[4]] <- model4_no_interaction # Override with no-interaction model
coef_table <- af_coef_and_ci_table(models, coef_names)
af_coef_and_ci_plot(coef_table, xpose = TRUE, title = "Social Dimension",
exp_ctrl = c(TRUE, TRUE, TRUE, TRUE, TRUE))
notes <- af_create_regression_notes(df, models = models, display_names = display_names, is_exp = TRUE,
show_significance = TRUE, significance_levels = c(0.05, 0.01, 0.001))
cov_labels <- af_cov_names(df, models, display_names)
af_stargazer(models = models, cov_labels = cov_labels, coef_exp = TRUE, notes = notes,
title = "Individual Extremist ~ Event Occurred x Political Orientation + Demographics")
Individual Extremist ~ Event Occurred x Political Orientation +
Demographics
|
|
|
|
Dependent variable:
|
|
|
|
|
|
i_sel
|
i_sel
|
i_sel
|
|
|
logistic
|
conditional
|
logistic
|
|
|
|
logistic
|
|
|
|
Inland Terror
|
Bennet Gov. Fall
|
Judicial Reform
|
Gallant Dismissal
|
Oct. 7th War
|
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
|
|
|
Event Occured[1]
|
1.265
|
0.772
|
1.018
|
|
1.774
|
|
|
(0.513)
|
(0.677)
|
(0.136)
|
|
(0.619)
|
|
Event Occured
|
|
|
|
0.948
|
|
|
|
|
|
|
(0.130)
|
|
|
Political Orientation[center]
|
4.005***
|
1.831
|
12.048*
|
4.770***
|
3.141*
|
|
|
(0.412)
|
(0.387)
|
(1.016)
|
(0.473)
|
(0.485)
|
|
Political Orientation[right]
|
10.189***
|
9.447***
|
32.068***
|
14.547***
|
9.668***
|
|
|
(0.392)
|
(0.349)
|
(1.003)
|
(0.457)
|
(0.462)
|
|
Gender[Female]
|
0.975
|
1.017
|
|
0.824
|
1.151
|
|
|
(0.099)
|
(0.114)
|
|
(0.122)
|
(0.111)
|
|
Age Group[31-45]
|
1.258
|
1.029
|
0.768
|
0.836
|
0.986
|
|
|
(0.129)
|
(0.148)
|
(0.184)
|
(0.161)
|
(0.149)
|
|
Age Group[46-60]
|
1.228
|
1.045
|
1.044
|
1.312
|
1.193
|
|
|
(0.139)
|
(0.159)
|
(0.183)
|
(0.159)
|
(0.151)
|
|
Age Group[60+]
|
1.401*
|
1.096
|
0.869
|
1.164
|
1.134
|
|
|
(0.155)
|
(0.172)
|
(0.215)
|
(0.206)
|
(0.181)
|
|
Event Occured[1] × Political Orientation[center]
|
0.458
|
1.531
|
|
|
0.570
|
|
|
(0.566)
|
(0.744)
|
|
|
(0.670)
|
|
Event Occured[1] × Political Orientation[right]
|
0.945
|
0.926
|
|
|
0.554
|
|
|
(0.524)
|
(0.690)
|
|
|
(0.631)
|
|
|
|
Observations
|
3,215
|
2,493
|
1,342
|
2,221
|
2,638
|
|
R2
|
|
|
0.055
|
|
|
|
|
|
Note: * p < 0.050; ** p < 0.010; *** p < 0.001. The reference
category for Event Occured is ‘0’. The reference category for Political
Orientation is ‘left’. The reference category for Gender is ‘Male’. The
reference category for Age Group is ‘18-30’. Standard errors in
parentheses. The coefficients of models 1 and 2 and 3 and 4 and 5 are
exponentiated.
|
Overall (Combined
Dimensions)
formula_str <- paste("i_oel ~ event_occurred * pe_left_center_right","+", d_fmla)
models <- af_wave_pair_regression(df, wave_var = wave_var, wave_list = wave_list,
formula_str = formula_str, regression_type = "Logit")
models[[3]] <- mp4 # Override with panel model
coef_table <- af_coef_and_ci_table(models, coef_names)
af_coef_and_ci_plot(coef_table, xpose = TRUE, title = "Overall (Combined Dimensions)",
exp_ctrl = c(TRUE, TRUE, TRUE, TRUE, TRUE))
notes <- af_create_regression_notes(df, models = models, display_names = display_names, is_exp = TRUE,
show_significance = TRUE, significance_levels = c(0.05, 0.01, 0.001))
cov_labels <- af_cov_names(df, models, display_names)
af_stargazer(models = models, cov_labels = cov_labels, coef_exp = TRUE, notes = notes,
title = "Individual Extremist ~ Event Occurred x Political Orientation + Demographics")
Individual Extremist ~ Event Occurred x Political Orientation +
Demographics
|
|
|
|
Dependent variable:
|
|
|
|
|
|
i_oel
|
i_oel
|
i_oel
|
|
|
logistic
|
conditional
|
logistic
|
|
|
|
logistic
|
|
|
|
Inland Terror
|
Bennet Gov. Fall
|
Judicial Reform
|
Gallant Dismissal
|
Oct. 7th War
|
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
|
|
|
Event Occured[1]
|
0.612
|
1.596
|
2.129
|
0.516
|
1.740
|
|
|
(0.359)
|
(0.447)
|
(0.592)
|
(0.435)
|
(0.410)
|
|
Political Orientation[center]
|
0.625
|
0.748
|
1.708
|
0.593
|
1.308
|
|
|
(0.306)
|
(0.359)
|
(0.548)
|
(0.415)
|
(0.342)
|
|
Political Orientation[right]
|
2.823***
|
5.448***
|
3.050*
|
1.295
|
3.071***
|
|
|
(0.244)
|
(0.288)
|
(0.513)
|
(0.340)
|
(0.312)
|
|
Gender[Female]
|
0.605***
|
0.601***
|
|
0.491***
|
0.693**
|
|
|
(0.104)
|
(0.119)
|
|
(0.128)
|
(0.117)
|
|
Age Group[31-45]
|
0.870
|
0.701*
|
0.828
|
0.888
|
0.893
|
|
|
(0.132)
|
(0.154)
|
(0.203)
|
(0.164)
|
(0.157)
|
|
Age Group[46-60]
|
0.867
|
0.780
|
1.091
|
1.109
|
1.128
|
|
|
(0.144)
|
(0.166)
|
(0.205)
|
(0.168)
|
(0.158)
|
|
Age Group[60+]
|
1.259
|
1.286
|
1.449
|
1.466
|
1.146
|
|
|
(0.154)
|
(0.167)
|
(0.211)
|
(0.203)
|
(0.187)
|
|
Event Occured[1] × Political Orientation[center]
|
1.195
|
1.419
|
0.348*
|
2.118
|
0.490
|
|
|
(0.471)
|
(0.554)
|
(0.687)
|
(0.538)
|
(0.485)
|
|
Event Occured[1] × Political Orientation[right]
|
1.899
|
0.418
|
0.410
|
2.286
|
0.416*
|
|
|
(0.376)
|
(0.467)
|
(0.614)
|
(0.463)
|
(0.432)
|
|
|
|
Observations
|
3,215
|
2,493
|
1,342
|
2,221
|
2,638
|
|
R2
|
|
|
0.020
|
|
|
|
|
|
Note: * p < 0.050; ** p < 0.010; *** p < 0.001. The reference
category for Event Occured is ‘0’. The reference category for Political
Orientation is ‘left’. The reference category for Gender is ‘Male’. The
reference category for Age Group is ‘18-30’. Standard errors in
parentheses. The coefficients of models 1 and 2 and 3 and 4 and 5 are
exponentiated.
|
Multicollinearity (VIF)
Test
formula_str <- paste("pe_overall ~ Wave * pe_left_center_right","+", d_fmla)
model <- lm(formula_str, data=df, na.action = na.omit)
result <- af_vif_test(model, interactions = TRUE)
print(result$interpretation)
[1] “We use VIF to test for multicollinearity. The results indicate
that all adjusted GVIF values are ≤ 2.is not a concern.adjusted GVIF
value: 1.01.”
| Multicollinearity Assessment (with Interactions) |
| Predictor |
Adjusted GVIF |
| Wave |
1.002 |
| pe_left_center_right |
1.002 |
| gender |
1.010 |
| age_group |
1.010 |
Robustness
Impact of Occurred
Events on the Dimensions
mp1 <- plm(pe_ideology ~ event_occurred , data = p_data, model = "within")
mp2 <- plm(pe_violence ~ event_occurred , data = p_data, model = "within")
mp3 <- plm(pe_intolerance ~ event_occurred , data = p_data, model = "within")
mp4 <- plm(pe_overall ~ event_occurred , data = p_data, model = "within")
formula_str <- "pe_ideology ~ event_occurred"
models <- af_wave_pair_regression(df, wave_var = wave_var, wave_list = wave_list,
formula_str = formula_str, regression_type = "OLS")
models[[3]] <- mp1 # Override with panel model
notes <- af_create_regression_notes(df, models = models, display_names = display_names,
show_significance = TRUE, significance_levels = c(0.05, 0.01, 0.001))
cov_labels <- af_cov_names(df, models, display_names)
af_stargazer(models = models, cov_labels = cov_labels, notes = notes,
title = "Cognitive Political Extremism ~ Event Occurred")
Cognitive Political Extremism ~ Event Occurred
|
|
|
|
Dependent variable:
|
|
|
|
|
|
pe_ideology
|
|
|
OLS
|
panel
|
OLS
|
|
|
|
linear
|
|
|
|
Inland Terror
|
Bennet Gov. Fall
|
Judicial Reform
|
Gallant Dismissal
|
Oct. 7th War
|
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
|
|
|
Event Occured[1]
|
-0.210**
|
-0.047
|
0.035
|
0.106
|
0.121
|
|
|
(0.068)
|
(0.074)
|
(0.054)
|
(0.084)
|
(0.073)
|
|
|
|
Observations
|
3,215
|
2,493
|
1,342
|
2,221
|
2,638
|
|
R2
|
0.003
|
0.0002
|
0.001
|
0.001
|
0.001
|
|
Adjusted R2
|
0.003
|
-0.0002
|
-1.000
|
0.0003
|
0.001
|
|
|
|
Note: * p < 0.050; ** p < 0.010; *** p < 0.001. The reference
category for Event Occured is ‘0’. Standard errors in parentheses.
|
formula_str <- "pe_violence ~ event_occurred"
models <- af_wave_pair_regression(df, wave_var = wave_var, wave_list = wave_list,
formula_str = formula_str, regression_type = "OLS")
models[[3]] <- mp2 # Override with panel model
notes <- af_create_regression_notes(df, models = models, display_names = display_names,
show_significance = TRUE, significance_levels = c(0.05, 0.01, 0.001))
cov_labels <- af_cov_names(df, models, display_names)
af_stargazer(models = models, cov_labels = cov_labels, notes = notes,
title = "Behavioral Political Extremism ~ Event Occurred")
Behavioral Political Extremism ~ Event Occurred
|
|
|
|
Dependent variable:
|
|
|
|
|
|
pe_violence
|
|
|
OLS
|
panel
|
OLS
|
|
|
|
linear
|
|
|
|
Inland Terror
|
Bennet Gov. Fall
|
Judicial Reform
|
Gallant Dismissal
|
Oct. 7th War
|
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
|
|
|
Event Occured[1]
|
0.075*
|
-0.038
|
0.005
|
0.054
|
0.034
|
|
|
(0.034)
|
(0.042)
|
(0.032)
|
(0.044)
|
(0.038)
|
|
|
|
Observations
|
3,215
|
2,493
|
1,342
|
2,221
|
2,638
|
|
R2
|
0.001
|
0.0003
|
0.00004
|
0.001
|
0.0003
|
|
Adjusted R2
|
0.001
|
-0.0001
|
-1.001
|
0.0002
|
-0.0001
|
|
|
|
Note: * p < 0.050; ** p < 0.010; *** p < 0.001. The reference
category for Event Occured is ‘0’. Standard errors in parentheses.
|
formula_str <- "pe_intolerance ~ event_occurred"
models <- af_wave_pair_regression(df, wave_var = wave_var, wave_list = wave_list,
formula_str = formula_str, regression_type = "OLS")
models[[3]] <- mp3 # Override with panel model
notes <- af_create_regression_notes(df, models = models, display_names = display_names,
show_significance = TRUE, significance_levels = c(0.05, 0.01, 0.001))
cov_labels <- af_cov_names(df, models, display_names)
af_stargazer(models = models, cov_labels = cov_labels, notes = notes,
title = "Social Political Extremism ~ Event Occurred")
Social Political Extremism ~ Event Occurred
|
|
|
|
Dependent variable:
|
|
|
|
|
|
pe_intolerance
|
|
|
OLS
|
panel
|
OLS
|
|
|
|
linear
|
|
|
|
Inland Terror
|
Bennet Gov. Fall
|
Judicial Reform
|
Gallant Dismissal
|
Oct. 7th War
|
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
|
|
|
Event Occured[1]
|
0.0004
|
-0.001
|
-0.057
|
0.000
|
0.000
|
|
|
(0.055)
|
(0.066)
|
(0.052)
|
(0.073)
|
(0.063)
|
|
|
|
Observations
|
3,215
|
2,493
|
1,342
|
2,221
|
2,638
|
|
R2
|
0.000
|
0.00000
|
0.002
|
0.000
|
0.000
|
|
Adjusted R2
|
-0.0003
|
-0.0004
|
-0.998
|
-0.0005
|
-0.0004
|
|
|
|
Note: * p < 0.050; ** p < 0.010; *** p < 0.001. The reference
category for Event Occured is ‘0’. Standard errors in parentheses.
|
formula_str <- "pe_overall ~ event_occurred"
models <- af_wave_pair_regression(df, wave_var = wave_var, wave_list = wave_list,
formula_str = formula_str, regression_type = "OLS")
models[[3]] <- mp4 # Override with panel model
notes <- af_create_regression_notes(df, models = models, display_names = display_names,
show_significance = TRUE, significance_levels = c(0.05, 0.01, 0.001))
cov_labels <- af_cov_names(df, models, display_names)
af_stargazer(models = models, cov_labels = cov_labels, notes = notes,
title = "Overall Political Extremism ~ Event Occurred")
Overall Political Extremism ~ Event Occurred
|
|
|
|
Dependent variable:
|
|
|
|
|
|
pe_overall
|
|
|
OLS
|
panel
|
OLS
|
|
|
|
linear
|
|
|
|
Inland Terror
|
Bennet Gov. Fall
|
Judicial Reform
|
Gallant Dismissal
|
Oct. 7th War
|
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
|
|
|
Event Occured[1]
|
-0.078*
|
-0.013
|
-0.006
|
0.050
|
0.057
|
|
|
(0.035)
|
(0.039)
|
(0.030)
|
(0.044)
|
(0.038)
|
|
|
|
Observations
|
3,215
|
2,493
|
1,342
|
2,221
|
2,638
|
|
R2
|
0.002
|
0.00004
|
0.0001
|
0.001
|
0.001
|
|
Adjusted R2
|
0.001
|
-0.0004
|
-1.001
|
0.0001
|
0.001
|
|
|
|
Note: * p < 0.050; ** p < 0.010; *** p < 0.001. The reference
category for Event Occured is ‘0’. Standard errors in parentheses.
|
1.3 Social Dimension