table_1 <-
mapply(FUN = analyses,
MoreArgs = list(DV = "school_grade",
treat = "treat",
FE = "ethnicity",
data = data_individual),
covs = list(column_1 = c("male", "income"),
column_1_rep = c("male", "income"),
column_2 = NULL,
column_2_rep = NULL),
heterogenous = list(NULL,"iq", NULL, "iq"),
subset = list("iq >= 50", NULL, "iq >= 50", NULL),
status = list(c(F,T,T), c(T,T,F), c(F,T,T), c(T,F,F) ),
USE.NAMES = TRUE)
table_2 <-
mapply(FUN = analyses,
MoreArgs = list(DV = "turnout",
treat = "treat",
FE = "urban",
data = data_admin),
covs = list(column_1 = c("age", "school_grade"),
column_1_rep = c("age", "school_grade"),
column_2 = c("height", "income"),
column_3 = c("age", "school_grade", "height", "income"),
column_3_rep = c("age", "school_grade", "height", "income")
),
heterogenous = list(NULL,"iq", NULL, NULL, "iq"),
subset = list("iq >= 50", NULL, "iq >= 50", "iq >= 50", NULL),
status = list(c(F,T,T), c(T,T,F), c(T,T,T), c(F,T,T), c(T,F,F) ),
USE.NAMES = TRUE)
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