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:
-
Add dependencies!!
-
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="camillemmoore/informativeDropout", ref="develop")
- Load the library
library(informativeDropout)
Instructions for replicating results in "A Bayesian Natural Cubic B Spline Varying Coefficient Method for Non-Ignorable Dropout"
TBD
Instructions for replicating results in "A Dirichlet Process Mixture Model for Non-Ignorable Dropout"
TBD