pmrm: Progression Models for Repeated Measures

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>.

Version:	0.0.4
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)
Published:	2026-04-03
DOI:	10.32614/CRAN.package.pmrm
Author:	William Michael Landau [aut, cre], Lars Lau Raket [aut], Kasper Kristensen [aut], Eli Lilly and Company [cph, fnd]
Maintainer:	William Michael Landau <will.landau.oss at gmail.com>
BugReports:	https://github.com/openpharma/pmrm/issues
License:	MIT + file LICENSE
URL:	https://github.com/openpharma/pmrm, https://openpharma.github.io/pmrm/
NeedsCompilation:	no
Language:	en-US
Citation:	pmrm citation info
Materials:	README, NEWS
CRAN checks:	pmrm results

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