We introduce an R package PGEE that implements the penalized generalized estimating equations (GEE) procedure proposed by Wang et al. (2012) to analyze longitudinal data with a large number of covariates. The PGEE package includes three main functions: CVfit, PGEE, and MGEE. The CVfit function computes the cross-validated tuning parameter for penalized generalized estimating equations. The function PGEE performs simultaneous estimation and variable selection for longitudinal data with high-dimensional covariates; whereas the function MGEE fits unpenalized GEE to the data for comparison. The R package PGEE is illustrated using a yeast cell-cycle gene expression data set.
gee, geepack, PGEE, MASS, mvtnorm, ncvreg, penalized, glmnet, rqPen
MachineLearning, SocialSciences, Distributions, Econometrics, Multivariate, Survival, Environmetrics, Finance, NumericalMathematics, Psychometrics, Robust
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For attribution, please cite this work as
Inan & Wang, "The R Journal: PGEE: An R Package for Analysis of Longitudinal Data with High-Dimensional Covariates", The R Journal, 2017
BibTeX citation
@article{RJ-2017-030,
author = {Inan, Gul and Wang, Lan},
title = {The R Journal: PGEE: An R Package for Analysis of Longitudinal Data with High-Dimensional Covariates},
journal = {The R Journal},
year = {2017},
note = {https://doi.org/10.32614/RJ-2017-030},
doi = {10.32614/RJ-2017-030},
volume = {9},
issue = {1},
issn = {2073-4859},
pages = {393-402}
}