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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 thesimglm 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 thesimglm 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
  • Specify floor or ceiling aspects of continuous attributes
  • 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), Poisson (count), ordinal (rating scale) outcome variables.
• Cross classified simulation and power

Bugs and feature requests are welcomed. Please track these on GitHub here:https://github.com/lebebr01/simglm/issues. I'm also open to pull requests.

Enjoy!