Regression simulation function

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.
• Simulation of missing data

Features coming soon:

• Include missing data in power simulation designs.
• More options for simulating random components
• Ability to simulate different distributions for different random effects
• Ability to specify correlation amount random effects individually.
• Expand variance of mixture distribution function to include unequal weighting.

Package Installation

This package can be installed by using the devtools package.

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

Introduction to the simglm package

The best way to become oriented with the simglm package is through the package vignette. There are two ways to get to the vignette (both will open a browser to view the vignette):

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

Note: 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)

Enjoy!