Sample Size and Simulation for Negative Binomial Outcomes.

gsDesignNB

gsDesignNB provides design, simulation, and interim monitoring tools for recurrent-event trials analyzed with negative binomial rate models, with Poisson methods available as the limiting special case when dispersion is negligible.

The package is NB-first: plan designs with sample_size_nbinom(), simulate recurrent-event data with nb_sim() or nb_sim_seasonal(), and evaluate group sequential monitoring or sample size re-estimation with sim_gs_nbinom() and sim_ssr_nbinom(). Planning and simulation can use either Wald or score-test inference for rate ratios. The gsDesign package supplies the underlying spending-function and boundary calculations used by those workflows.

Start Here

• sample-size-nbinom for fixed-design planning
• score-vs-wald-simulation for Wald/score sizing and Type I error guidance
• simulation-example and seasonal-simulation for recurrent-event data generation
• ssr-example and ssr-simulation-study for negative binomial SSR workflows

Installation

You can install gsDesignNB from CRAN with:

install.packages("gsDesignNB")

Or install the development version from GitHub with:

remotes::install_github("keaven/gsDesignNB")

Code style

This package follows the tidyverse style guide.