--- title: "RMSTpowerBoost Home" name: RMSTpowerBoost-Home description: "Overview of the package, guides, installation, and application links." output: rmarkdown::html_vignette: toc: true fig_caption: true code_folding: hide self_contained: true vignette: > %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} %\VignetteIndexEntry{RMSTpowerBoost Home} %\VignetteName{RMSTpowerBoost-Home} %\VignetteDepends{RMSTpowerBoost} --- # RMSTpowerBoost `RMSTpowerBoost` provides power and sample size tools for study designs that use restricted mean survival time (RMST). The package supports direct RMST modeling with analytical and bootstrap-based procedures for settings that include linear covariate adjustment, stratification, semiparametric additive effects, and covariate-dependent censoring. The package includes both an R interface and a Shiny application. ## Guides - [Main package guide](https://uthsc-zhang.github.io/RMSTpowerBoost-Package/articles/RMSTpowerBoost-Main.html) - [Data generation guide](https://uthsc-zhang.github.io/RMSTpowerBoost-Package/articles/RMSTpowerBoost-DataGen.html) - [Shiny application guide](https://uthsc-zhang.github.io/RMSTpowerBoost-Package/articles/RMSTpowerBoost-App.html) ## Key Features - Linear IPCW-based RMST power and sample size calculations. - Additive and multiplicative stratified models for multi-center or highly stratified studies. - Bootstrap-based semiparametric GAM procedures for nonlinear covariate effects. - Analytical and simulation-based methods for covariate-dependent censoring under a single censoring mechanism. ## Installation Install the development version from GitHub: ```r install.packages("remotes") remotes::install_github("UTHSC-Zhang/RMSTpowerBoost-Package") ``` ## Shiny App Interactive web application: -