The informativeDropout package for R (>3.2.0) implements several models to account for dropout in longitudinal studies.

The package provides companion code for the manuscripts:

Moore, C.M., Carlson, N.E., MaWhinney, S. A Bayesian Natural Cubic B Spline Varying Coefficient Method for Non-Ignorable Dropout, In review.

Moore, C.M., Carlson, N.E., MaWhinney, S. A Dirichlet Process Mixture Model for Non-Ignorable Dropout, In review.

The results in the above manuscript were produced using R version 3.2.4. To reproduce the results, perform the following steps:

• Install R version 3.2.x or higher by following the instructions at http://www.r-project.org
• From the R environment, install and load the "devtools" package

install.packages("devtools")
library(devtools)

• Install the "informativeDropout" package directly from Github.com

install_github(repo="kreidles/informativeDropout", ref="develop")

• Load the library

library(informativeDropout)

Install the informativeDropout package as described above.

Run the DP model demo program

demo(ba_dp_paper)

The demo will run for 200,000 iterations may take up to 24 hours to run, depending on processor speed.

Install the informativeDropout package as described above.

Run the DP model demo program

demo(smmr_spline_paper)