Sample Size and Simulation for Negative Binomial Outcomes R package gsDesignNB version 0.3.2 Provides tools for planning and simulating recurrent event trials with overdispersed count endpoints analyzed using negative binomial (or Poisson) rate models. Implements sample size and power calculations for fixed designs with variable accrual, dropout, maximum follow-up, and event gaps, including methods of Zhu and Lakkis (2014) <doi:10.1002/sim.5947> and Friede and Schmidli (2010) <doi:10.3414/ME09-02-0060> as well as extensions for score-test sizing and gaps between events. Supports group sequential monitoring by building on the 'gsDesign' package. Includes recurrent-event simulation utilities (including seasonal rates), interim data truncation, Wald and score-test inference for rate ratios, and information estimation and sample size re-estimation with or without treatment-group labels. Software Depends: R (>= 4.1.0) Imports: data.table, gsDesign (>= 3.10.0), simtrial, stats, MASS Suggests: glmmTMB, httpuv, testthat (>= 3.0.0), knitr, rmarkdown, ggplot2, dplyr, gt, scales, shiny, foreach, doFuture, future, future.apply, gridExtra Keaven Anderson <keaven_anderson@merck.com> Comprehensive R Archive Network (CRAN) Keaven Anderson [aut, cre], Hongtao Zhang [aut], Andrea Maes [aut], Nan Xiao [ctb], Merck & Co., Inc., Rahway, NJ, USA and its affiliates [cph] (ROR: <https://ror.org/02891sr49>) GPL (>= 3) 2026-07-06 application/tgz https://CRAN.R-project.org/package=gsDesignNB doi:10.32614/CRAN.package.gsDesignNB