Nothing
library(testthat)
suppressMessages(library(lavaan))
check_gen_dat <- function(model,
pop_es,
n = 10000,
seed = NULL) {
set.seed(seed)
ptable <- ptable_pop(model,
pop_es = pop_es,
standardized = TRUE)
mm_out <- model_matrices_pop(ptable)
mm_lm_out <- mm_lm(mm_out)
mm_lm_dat_out <- mm_lm_data(mm_lm_out,
n = n)
out <- list(ptable = ptable,
mm_out = mm_out,
mm_lm_out = mm_lm_out,
mm_lm_dat_out = mm_lm_dat_out)
out
}
test_that("add_indicator_scores", {
# Simple mediation model
model_simple_med <-
"
m ~ x
y ~ m + x
"
model_simple_med_es <- c(".beta." = "m",
"m ~ x" = "l",
"y ~ x" = "n")
check_out <- check_gen_dat(model_simple_med,
model_simple_med_es,
seed = 1234)
dat <- as.matrix(check_out$mm_lm_dat_out)
head(dat)
dat0 <- add_indicator_scores(dat,
ps = c(x = 4, m = 2),
rels = c(x = .30, m = .70))
expect_setequal(colnames(dat0),
c("y", "x1", "x2", "x3", "x4", "m1", "m2"))
dat0 <- add_indicator_scores(dat,
ps = c(x = 4, m = 2),
rels = c(x = .30, m = .70),
keep_f_scores = TRUE)
expect_setequal(colnames(dat0),
c("m", "y", "x", "x1", "x2", "x3", "x4", "m1", "m2"))
dat0 <- add_indicator_scores(dat,
ps = c(x = 4, m = 2, y = 10),
rels = c(x = .30, m = .70, y = .90))
expect_false(any(c("x", "m", "y") %in% colnames(dat0)))
expect_error(add_indicator_scores(dat,
ps = c(x = 4, m = 2, y2 = 10),
rels = c(x = .30, m = .70, y = .90)))
expect_error(add_indicator_scores(dat,
ps = c(x = 4, m = 2),
rels = c(x = .30, m = .70, y = .90)))
expect_error(add_indicator_scores(dat,
ps = c(x = 4, m = 2, z = 10),
rels = c(x = .30, m = .70, z = .90)))
})
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