Best sim results so far

R/30-data_gen_complex.R

@@ -100,7 +100,7 @@ make_population <- function(model_no = 1, seed = 123, H1 = FALSE,
 
   # Stratify according to latent variable --------------------------------------
   abil_order <-
-    as_tibble(eta) %>%
+    as_tibble(eta[, 1]) %>%
     mutate(z = rowSums(across(everything())),
            rn = row_number()) %>%
     select(z, rn) %>%
@@ -300,7 +300,7 @@ gen_data_bin_complex3 <- function(population = make_population(1, seed = NULL),
     group_by(type) %>%
     mutate(pr_school_selected = npsu / dplyr::n(),
            prob = pr_school_selected * pr_class_selected,
-           stratum_wt = dplyr::n() / total_type,
+           stratum_wt = 1,  # dplyr::n() / total_type,
            wt = 1 / (prob * stratum_wt))
 
   # Sampling of PSUs

R/50-sim_functions.R

@@ -51,7 +51,7 @@ run_ligof_sims <- function(model_no = 1, nsim = 1000, samp_size = 1000,
                                     "strat2"),
                            simtype = c("type1", "power"), starting_seed = 16423,
                            ncores = parallel::detectCores() - 2,
-                           pop_Sigma = FALSE, Sigma2 = NULL) {
+                           pop_Sigma = FALSE, Sigma2 = NULL, the_wt = NULL) {
 
   # Model setup ----------------------------------------------------------------
   mod <- txt_mod(model_no)
@@ -60,10 +60,10 @@ run_ligof_sims <- function(model_no = 1, nsim = 1000, samp_size = 1000,
   if (simtype == "power") H1 <- TRUE
   samp <- match.arg(samp, c("srs", "wtd", "strat", "clust", "strcl", "strat2"))
 
-  the_wt <- NULL
+  # the_wt <- NULL
   if (samp != "srs") {
-    the_wt <- "wt"
-    pop <- make_population(model_no, seed = starting_seed, H1 = H1,
+    # the_wt <- "wt"
+    pop <- make_population(model_no, seed = 27324, H1 = H1,
                            Sigma2_attr = isTRUE(pop_Sigma))
     Sigma2pop <- attr(pop, "Sigma2")
   }

data-raw/07-run_simulations.R

@@ -1,25 +1,23 @@
 library(tidyverse)
 library(lavaan.bingof)
-library(survey)
 analysis_path <- dirname(rstudioapi::getSourceEditorContext()$path)
 
 # All simulations --------------------------------------------------------------
 for (sim_type in c("type1")) {
-  for (samp_method in c("strat")) {
-    for (the_samp_size in c(1000)) {
-      for (mod_no in c(4)) {
+  for (samp_method in c("strcl")) {
+    for (the_samp_size in c(5000, 10000)) {
+      for (mod_no in 3) {
         sim_name <- paste0(samp_method, mod_no, "_n", the_samp_size, "_",
                            sim_type)
         cat("[", as.character(Sys.time()), "]", "Now running simulation",
             sim_name, "\n")
-        sim <- run_ligof_sims(mod_no, samp_size = the_samp_size, nsim = 100,
+        sim <- run_ligof_sims(mod_no, samp_size = the_samp_size, nsim = 1000,
                               samp = samp_method, simtype = sim_type,
-                              starting_seed = NULL,
-                              pop_Sigma = FALSE, Sigma2 = "theoretical",
-                              the_wt = NULL)
+                              starting_seed = NULL, the_wt = NULL,
+                              pop_Sigma = FALSE, Sigma2 = "theoretical")
         invisible(list2env(setNames(list(sim), sim_name), envir = .GlobalEnv))
-        # save(list = sim_name, file = paste0(analysis_path, "/Rsave/",
-        #                                     sim_name, ".RData"))
+        save(list = sim_name, file = paste0(analysis_path, "/Rsave/",
+                                            sim_name, ".RData"))
       }
     }
   }