We describe a new package called pseval that implements the core methods for the evaluation of principal surrogates in a single clinical trial. It provides a flexible interface for defining models for the risk given treatment and the surrogate, the models for integration over the missing counterfactual surrogate responses, and the estimation methods. Estimated maximum likelihood and pseudo-score can be used for estimation, and the bootstrap for inference. A variety of post-estimation methods are provided, including print, summary, plot, and testing. We summarize the main statistical methods that are implemented in the package and illustrate its use from the perspective of a novice R user.
pseval, survival, survey, ggplot2, lattice, Surrogate
Graphics, SocialSciences, Survival, ClinicalTrials, Econometrics, Multivariate, OfficialStatistics, Pharmacokinetics, Phylogenetics
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For attribution, please cite this work as
Sachs & Gabriel, "The R Journal: An Introduction to Principal Surrogate Evaluation with the pseval Package", The R Journal, 2016
BibTeX citation
@article{RJ-2016-046,
author = {Sachs, Michael C. and Gabriel, Erin E.},
title = {The R Journal: An Introduction to Principal Surrogate Evaluation with the pseval Package},
journal = {The R Journal},
year = {2016},
note = {https://doi.org/10.32614/RJ-2016-046},
doi = {10.32614/RJ-2016-046},
volume = {8},
issue = {2},
issn = {2073-4859},
pages = {277-292}
}