Bias and Uncertainty Corrected Sample Size R package BUCSS version 2.0.0 Implements sample size planning for a future study from the summary statistics of a prior study, correcting the prior effect for publication bias and uncertainty so the planned study attains its target statistical power more reliably than methods that take a sample effect size at face value. Planners cover the one-sample, paired, independent, and Welch t tests; between-subjects analysis of variance and covariance; within-subjects and split-plot analysis of variance; a regression coefficient, the squared multiple correlation, and a subset of predictors; the Pearson correlation; a two-group multivariate comparison; and the chi square difference between nested models. The regression planners can treat the predictors as fixed or as sampled, the within-subjects and split-plot planners accept a sphericity correction, and each plan reports the effect size it is built on. A simulation function audits how often a plan attains its target power. The method is described in Anderson, Kelley, and Maxwell (2017) <doi:10.1177/0956797617723724> and extended to replication studies in Anderson and Kelley (2024) <doi:10.1037/met0000520>. Software Depends: R (>= 3.6.0) Imports: generics, graphics, stats, withr (>= 3.0.3) Suggests: testthat (>= 3.1.7), knitr, rmarkdown Ken Kelley <kkelley@nd.edu> Comprehensive R Archive Network (CRAN) Ken Kelley [aut, cre] (ORCID: <https://orcid.org/0000-0002-4756-8360>), Samantha F. Anderson [aut] (ORCID: <https://orcid.org/0000-0003-4451-5295>), Scott E. Maxwell [aut] (ORCID: <https://orcid.org/0000-0001-8067-7027>) GPL (>= 3) 2026-10-13 application/tgz https://CRAN.R-project.org/package=BUCSS doi:10.32614/CRAN.package.BUCSS en-US