# NOT RUN {
data(test_data)
library(glmmTMB)
## where subj is some RE
test_model <- glmmTMB(y ~ x_var1 + (1 | subj),
data = test_data,
family = binomial)
output_list1 <- bootstrap_model(
test_model, base_data = test_data, 99, return_coefs_instead = TRUE)
output_list2 <- bootstrap_model(
test_model, base_data = test_data, 100, return_coefs_instead = TRUE)
output_list3 <- bootstrap_model(
test_model, base_data = test_data, 100, return_coefs_instead = TRUE)
combine_resampled_lists(output_list1, output_list2, output_list3)
num_blocks = 10
num_total_resamples = 299
reg_list <- list()
for(i in 1:num_blocks){
if(i < num_blocks){
block_resamples = floor((num_total_resamples + 1)/num_blocks)
} else {
block_resamples = floor((num_total_resamples + 1)/num_blocks - 1)
}
reg_list[[i]] = bootstrap_model(test_model,
base_data = test_data,
resamples = block_resamples,
return_coefs_instead = TRUE,
num_cores = 1) ## increase for parallel
}
boot_ci1 <- combine_resampled_lists(reg_list)
full_list <- combine_resampled_lists(reg_list, return_combined_list = TRUE)
boot_ci2 <- bootstrap_ci(full_list$base_coef_se,
full_list$resampled_coef_se)
identical(boot_ci1, boot_ci2)
# }
# NOT RUN {
# }
Run the code above in your browser using DataLab