README.md
In simglm: Simulate Models Based on the Generalized Linear Model

`simglm`: Tidy simulation and power analyses

This package can be directly installed through CRAN:

install.packages("simglm")

The development version of the package can be installed by using the devtools package.

library(devtools)
install_github("lebebr01/simglm")

The best way to become oriented with the simglm package is through the package vignette. There are two ways to get to the vignettes (both will open a browser to view the vignette). Below is an example loading the "Intro" vignette directly:

browseVignettes()
vignette("Intro", package = "simglm")

Note: If you install the development version of the package, you may need to tell R to build the vignettes when installing the simglm package by doing the following:

install_github("lebebr01/simglm", build_vignettes = TRUE)

A flexible suite of functions to simulate nested data. Currently supports the following features:

Longitudinal data simulation
Three levels of nesting
Specification of distribution of random components (random effects and random error)
Specification of serial correlation
Specification of the number of variables
- Ability to add time-varying covariates
- Specify the mean and variance of fixed covariate variables
- Factor variable simulation
- Ordinal variable simulation
Generation of mixture normal distributions
Cross sectional data simulation
Single level simulation
Power by simulation
- Vary parameters for a factorial simulation design.
- Can vary model fitted to the data to misspecify directly.
Simulation of missing data
Include other distributions for covariate simulation.
Continuous, Logistic (dichotomous), and Poisson (count) outcome variables.
Cross classified simulation and power