Description
Methods for Evaluating Principal Surrogates of Treatment Response.
Description
Contains the core methods for the evaluation of principal surrogates in a single clinical trial. 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 summary methods are provided, including print, summary, plot, and testing.
README.md
pseval: Methods for Evaluating Principal Surrogates of Treatment Response
Installation
pseval is an R package aimed at implementing existing methods for surrogate evaluation using a flexible and common interface. Development will take place on the Github page, and the current version of the package can be installed as shown below. First you must install the devtools package, if you haven't already install.packages("devtools").
devtools::install_github("sachsmc/pseval")
Check out the vignette for methodological details and information on how to use the package.
Check out the cheat sheet for a quick reference.
References
- Sachs and Gabriel, 2016. An Introduction to Principal Surrogate Evaluation with the pseval Package
- Gabriel and Gilbert, 2014. Evaluating principal surrogate endpoints with time-to-event data accounting for time-varying treatment efficacy
- Huang and Gilbert, 2011. Comparing Biomarkers as Principal Surrogate Endpoints
- Gilbert and Hudgens, 2008. Evaluating Candidate Principal Surrogate Endpoints
- Huang, Gilbert, and Wolfson, 2013. Design and Estimation for Evaluating Principal Surrogate Markers in Vaccine Trials.