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### ANALYTIC REPLICATIONS OF NOAH CARL'S Explaining Terrorism Threat Level Across Western Countries | |
# libs -------------------------------------------------------------------- | |
library(pacman) | |
p_load(XLConnect, kirkegaard, psych, weights, magrittr, effsize, lsr, compute.es, MASS) | |
# data -------------------------------------------------------------------- | |
d_main = readWorksheetFromFile(file = "Terrorism Threat.xlsx", sheet = 2) | |
rownames(d_main) = d_main$country | |
# derived variables ------------------------------------------ | |
#dummies | |
d_main$west = as.logical(d_main$west) | |
d_main$europe = as.logical(d_main$europe) | |
d_main$turkey = as.logical(d_main$turkey) | |
#muslim 2015 estimation | |
d_main$muslim15 = d_main$muslim10 + .25 * (d_main$muslim30 - d_main$muslim10) | |
#death count | |
d_main$deaths2 = log(1 + d_main$deaths) | |
#log gdp | |
d_main$gdp_log = log(d_main$gdpcap14) | |
#factors | |
d_main$any_num = d_main$any | |
d_main$any = as.factor(d_main$any) | |
d_main$part = as.factor(d_main$part) | |
d_main$terror_f = as.factor(d_main$terror) | |
#winzor turkey's value | |
d_main["Turkey", "muslim15"] = 19.075 | |
# subsets ----------------------------------------------------------------- | |
d_west = d_main[d_main$west, ] | |
d_euro = d_main[d_main$europe, ] | |
# descriptive ------------------------------------------------------------- | |
#threat level | |
psych::describe(d_west$terror) | |
#muslims | |
psych::describe(d_west$muslim15) | |
#deaths | |
psych::describe(d_west$deaths) | |
#any | |
table(d_west$any) | |
#against isis | |
table(d_west$part) | |
# cors -------------------------------------------------------------------- | |
wtd.cors(d_west) | |
cor.test(d_west$terror, d_west$muslim15) | |
cor.test(d_west$terror, d_west$deaths2) | |
# simple lm's --------------------------------------------------------------------- | |
lm("terror ~ poly(muslim15, 1)", data = d_west) %>% summary() | |
lm("terror ~ poly(muslim15, 2)", data = d_west) %>% summary() | |
lm("terror ~ poly(deaths2, 1)", data = d_west) %>% summary() | |
lm("terror ~ poly(deaths2, 2)", data = d_west) %>% summary() | |
# SMD --------------------------------------------------------------------- | |
#calculate the d | |
SMD_matrix(d_west$terror, d_west$any) | |
cohen.d(d = d_west$terror, f = as.factor(d_west$any)) | |
SMD_matrix(d_west$terror, d_west$part) | |
cohen.d(d = d_west$terror, f = as.factor(d_west$part)) | |
#try to get a p value | |
des(d = cohen.d(d = d_west$terror, f = d_west$any)$estimate, n.1 = 21, n.2 = 7) | |
des(d = cohen.d(d = d_west$terror, f = d_west$part)$estimate, n.1 = 21, n.2 = 7) | |
# complex lm's ------------------------------------------------------------ | |
#all west | |
d_betas = MOD_APSLM(dependent = "terror", predictors = c("muslim15", "any", "deaths2", "part", "gdp_log", "unemp14", "ineq0911"), data = d_west)[[1]] %>% round(2) | |
#the models we want | |
d_betas[c(8:10, 108, 112, 113), ] | |
#all oecd | |
d_betas = MOD_APSLM(dependent = "terror", predictors = c("muslim15", "any", "deaths2", "part", "gdp_log", "unemp14", "ineq0911"), data = d_main)[[1]] %>% round(2) | |
#the models we want | |
d_betas[c(8:10, 108, 112, 113), ] | |
#europe only | |
d_betas = MOD_APSLM(dependent = "terror", predictors = c("muslim15", "any", "deaths2", "part", "gdp_log", "unemp14", "ineq0911"), data = d_euro)[[1]] %>% round(2) | |
#the models we want | |
d_betas[c(8:10, 108, 112, 113), ] | |
#logistic | |
polr("terror_f ~ muslim15 + any", data = d_west) %>% summary() | |
polr("terror_f ~ muslim15 + deaths2", data = d_west) %>% summary() | |
polr("terror_f ~ muslim15 + part", data = d_west) %>% summary() | |
#lasso | |
d_betas_lasso = MOD_repeat_cv_glmnet(df = d_west, dependent = "terror", predictors = c("muslim15", "any", "deaths2", "part", "gdp_log", "unemp14", "ineq0911"), runs = 500) | |
MOD_summarize_models(d_betas_lasso) |
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