tests/testthat/test_print_all_cond_indirect_effects.R

In manymome: Mediation, Moderation and Moderated-Mediation After Model Fitting

library(testthat)
library(manymome)
suppressMessages(library(lavaan))

test_that("print all conditions", {
dat <- modmed_x1m3w4y1
n <- nrow(dat)
set.seed(860314)
dat$gp <- sample(c("gp1", "gp2", "gp3"), n, replace = TRUE)
dat$city <- sample(c("alpha", "beta", "gamma", "sigma"), n, replace = TRUE)
lm_m1 <- lm(m1 ~ x * w1, dat)
lm_m2 <- lm(m2 ~ m1 + gp + city, dat)
lm_m3 <- lm(m3 ~ m1 + x * gp, dat)
lm_y <- lm(y ~ m2 + m3 + x * w4, dat)
lm_m1_mm <- model.matrix(lm_m1)[, 4]
lm_m2_mm <- model.matrix(lm_m2)[, -c(1:2)]
lm_m3_mm <- model.matrix(lm_m3)[, 6:7]
lm_y_mm <- model.matrix(lm_y)[, 6]
dat2 <- cbind(dat, lm_m1_mm, lm_m2_mm, lm_m3_mm, lm_y_mm)
fit <- list(lm_m1, lm_m2, lm_m3, lm_y)

out_mm_1 <- mod_levels_list("w4", c("gpgp2", "gpgp3"), fit = fit, merge = TRUE)

out_1 <- cond_indirect_effects(wlevels = out_mm_1, x = "x", y = "y", m = "m3", fit = fit)

expect_output(print_all_cond_indirect_effects(out_1),
              "Moderator Level")

out_2 <- cond_effects(x = "x", y = "m1", wlevels = c("w1"), fit = lm_m1)
expect_output(print_all_cond_effects(out_2, digits = 2),
              "Moderator Level")
})