shzaidi / simglm

Regression simulation function

Regression simulation function

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

• Longitudinal data simulation
• Two levels of nesting
• Specification of distribution of random effects
• Specification of distribution of within cluster errors
• Specification of serial correlation
• Specification of population parameters *Including both fixed and random effects
• Specification of the number of variables
• Ability to add time-varying covariates
• Specify the mean and variance of fixed covariate variables
• Generation of mixture normal distributions
• Ability to compute variance of each normal distribution in each mixture distribution based on equal weighting.
• Cross sectional data simulation
• Single level simulation

Features coming soon:

• Adding factor variable simulation
• More options for simulating random components
• More distributions
• Ability to simulate different distributions for different random effects
• Power by simulation
• Missing Data
• 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)

Shiny Demo Application

There is a new shiny demo application. This is under ongoing development, therefore may be buggy or missing features. Check back regularly for updates.

Two ways to access shiny application (Note, you need to install locally the following packages: shiny, shinydashboard, DT, and simglm):

library(simglm)
run_shiny()

or

shiny::runGitHub('simglm', 'lebebr01', subdir = 'inst/shiny_examples/demo')

Enjoy!