Design and Modeling for Repeated Measures Studies R package RMeDPower2 version 1.0.1 Provides complete functionality to analyse data from repeated measures experiments with hierarchical or crossed experimental designs. Supports testing modeling assumptions, identifying outlier observations and experimental units, estimating statistical power, and performing sample size calculations. Uses linear mixed effects models via 'lme4' and simulation-based power analysis via 'simr'. Handles both normal and non-normal error distributions including binomial and Poisson families. For more details see Shin et al. (2022) <doi:10.1101/2022.07.18.500490>, Bates et al. (2015) <doi:10.18637/jss.v067.i01>, Green and MacLeod (2016) <doi:10.1111/2041-210X.12504>, Hartig (2024) <doi:10.32614/CRAN.package.DHARMa>, Nieuwenhuis et al. (2012) <doi:10.32614/RJ-2012-011>, Millard (2013) <doi:10.1007/978-1-4614-8456-1> and Kuznetsova et al. (2017) <doi:10.18637/jss.v082.i13>. Software Depends: R (>= 4.0) Imports: lme4, dplyr, simr, magrittr, ggplot2, ggtext, quantreg, tibble, lmerTest, DHARMa, influence.ME, EnvStats, jsonlite, methods, stats, grDevices, graphics Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Reuben Thomas <reuben.thomas@gladstone.ucsf.edu> Comprehensive R Archive Network (CRAN) Min-Gyoung Shin [aut], Reuben Thomas [aut, cre] GPL-3 2026-05-07 application/tgz https://CRAN.R-project.org/package=RMeDPower2 doi:10.32614/CRAN.package.RMeDPower2