#' srr_stats (tests) #' @srrstats {G5.6b} Conducts parameter recovery tests with multiple random seeds to validate consistency in results despite random components in data simulation or algorithms. #' @srrstats {RE3.2} Compares fixed effects estimated by `feglm` and `felm` with equivalent GLM models to ensure similarity. #' @srrstats {RE3.3} Validates the alignment of fixed effects recovery across different model implementations. #' @srrstats {RE4.3} Ensures robustness of fixed effects recovery under varied random seeds. #' @noRd NULL test_that("fixed_effects is similar to glm", { set.seed(200100) d <- data.frame( y = rnorm(100), x = rnorm(100), f = factor(sample(1:10, 1000, replace = TRUE)) ) fit1 <- glm(y ~ x + f + 0, data = d) fit2 <- feglm(y ~ x | f, data = d, family = gaussian()) c1 <- unname(coef(fit1)[grep("f", names(coef(fit1)))]) c2 <- unname(drop(fixed_effects(fit2)$f)) expect_equal(round(c1 - c2, 3), rep(0, 10)) set.seed(100200) d <- data.frame( y = rnorm(100), x = rnorm(100), f = factor(sample(1:10, 1000, replace = TRUE)) ) fit1 <- lm(y ~ x + f + 0, data = d) fit2 <- felm(y ~ x | f, data = d) c1 <- unname(coef(fit1)[grep("f", names(coef(fit1)))]) c2 <- unname(drop(fixed_effects(fit2)$f)) expect_equal(round(c1 - c2, 3), rep(0, 10)) })