Wrapper function for Type 1 and Power simulations

## Usage

```
run_ligof_sims(
model_no = 1,
nsim = 1000,
samp_size = 1000,
samp = c("srs", "wtd", "strat", "clust", "strcl", "strat2"),
simtype = c("type1", "power"),
starting_seed = 16423,
ncores = parallel::detectCores() - 2,
pop_Sigma = FALSE,
Sigma2 = NULL,
wt = NULL
)
```

## Arguments

- model_no
(integer) Choose from 1--5. See pkgdown articles for details.

- nsim
(integer) The number of simulations to conduct.

- samp_size
(integer) The exact sample size for SRS simulations or stratified sampling; otherwise the

*average*sample size for the other complex sampling methods.- samp
(character) Choose the sampling method for the simulated data. One of

`srs`

,`wtd`

,`strat`

,`clust`

or`strcl`

.- simtype
(character) Whether this is a

`type1`

simulation or`power`

simulation.- starting_seed
(integer) The starting random seed.

- ncores
(integer) The number of cores to use for parallelisation.

- pop_Sigma
(boolean) Should the population value for the multinomial covariance matrix be used, and not estimated?

- Sigma2
(for internal testing only) by default calculates (weighted) sample covariance

- wt
(character) Character vector indicating the column name of the sampling weights to use. Defaults to

`NULL`

.

## Value

A list of `tibble()`

s with the output from `all_tests()`

.

## Examples

```
if (FALSE) {
library(tidyverse)
library(lavaan.bingof)
analysis_path <- dirname(rstudioapi::getSourceEditorContext()$path)
# Run all scenarios described in manuscript
for (sim_type in c("type1", "power")) {
for (samp_method in c("srs", "strat", "clust", "strcl")) {
for (the_samp_size in c(500, 1000, 2000, 3000)) {
for (mod_no in 1:5) {
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,
samp = samp_method, simtype = sim_type)
invisible(list2env(setNames(list(sim), sim_name), envir = .GlobalEnv))
save(list = sim_name, file = paste0(analysis_path, "/Rsave/",
sim_name, ".RData"))
}
}
}
}
}
```