Script to meta-analyze results of lavaan sem models

ma_sem_model.R

# Script to meta-analyze results of lavaan sem models
# 
# Author: Brenton M. Wiernik
# Date: 2020-04-24
# License: CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/)
# 
# This script will meta-analyze the results of lavaan sem models. It assumes
# that the exact same lavaan model is specified for each sample and is
# not robust to differences in model specfications.# 

library(dplyr)
library(purrr)
library(data.table)
library(metafor)

# make a list of your fit lavaan models like this:

fit_models <- list(sample1 = fit_sample1, 
                   sample2 = fit_sample2, 
                   sample3 = fit_sample3)

coef_data <- fit_models %>% 
  map(~ c(coef(.x)) %>% 
        data.frame(param = names(.), 
                   coef = .)
      ) %>% 
  data.table::rbindlist(idcol = "sample")

vcov_data <- fit_models %>% 
  map(~ vcov(.x) %>% 
        as.data.frame() %>% 
        bind_cols(param = names(.), .) %>% 
        rename_at(-1, ~ paste0("v_", .x))
  ) %>% 
  data.table::rbindlist(idcol = "sample")

V_mat <- fit_models %>% 
  map(~ vcov(.x)) %>% 
  bldiag()

ma_data <- full_join(coef_data, vcov_data, by = c("sample", "param"))

ma_mod <- ma_data %>% 
  rma.mv(yi = coef, 
         V = V_mat,
         mods = ~ param - 1,
         random = ~ param | sample,
         struct = "UN",
         data = .
         )

ma_mod
predict(ma_mod)