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
- 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!