Progression Models for Repeated Measures R package pmrm version 0.0.4 A progression model for repeated measures (PMRM) is a continuous-time nonlinear mixed-effects model for longitudinal clinical trials in progressive diseases. Unlike mixed models for repeated measures (MMRMs), which estimate treatment effects as linear combinations of additive effects on the outcome scale, PMRMs characterize treatment effects in terms of the underlying disease trajectory. This framing yields clinically interpretable quantities such as average time saved and percent reduction in decline due to treatment. This package implements frequentist PMRMs by Raket (2022) <doi:10.1002/sim.9581> using 'RTMB' by Kristensen (2016) <doi:10.18637/jss.v070.i05>. Software Depends: R (>= 3.5.0) Imports: dplyr, generics, ggplot2, Matrix, nlme, RTMB (>= 1.8), rlang, stats, tibble, tidyselect, utils, vctrs Suggests: knitr, markdown, rmarkdown, readr, scales, testthat (>= 3.0.0) William Michael Landau <will.landau.oss@gmail.com> Comprehensive R Archive Network (CRAN) William Michael Landau [aut, cre] (ORCID: <https://orcid.org/0000-0003-1878-3253>), Lars Lau Raket [aut] (ORCID: <https://orcid.org/0000-0001-7099-2314>), Kasper Kristensen [aut] (ORCID: <https://orcid.org/0000-0003-3425-3762>), Eli Lilly and Company [cph, fnd] MIT + file LICENSE (https://CRAN.R-project.org/package=pmrm/LICENSE) 2026-04-03 application/tgz https://CRAN.R-project.org/package=pmrm doi:10.32614/CRAN.package.pmrm en-US