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splinetrials: Facilitate Clinical Trials Analysis Using Natural Cubic Splines

Create mixed models with repeated measures using natural cubic splines applied to an observed continuous time variable, as described by Donohue et al. (2023) <doi:10.1002/pst.2285>. Iterate through multiple covariance structure types until one converges. Categorize observed time according to scheduled visits. Perform subgroup analyses.

Version: 0.1.0
Imports: car, cli, dplyr, emmeans, mmrm (≥ 0.3.16), rlang, splines
Suggests: ggplot2, testthat (≥ 3.0.0)
Published: 2025-12-18
DOI: 10.32614/CRAN.package.splinetrials
Author: Nik Krieger [aut, cre], Daniel Sabanes Bove [ctb], Eli Lilly and Company [cph]
Maintainer: Nik Krieger <nikkrieger at gmail.com>
BugReports: https://github.com/NikKrieger/splinetrials/issues
License: Apache License (≥ 2)
URL: https://github.com/NikKrieger/splinetrials, https://nikkrieger.github.io/splinetrials/
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: splinetrials results

Documentation:

Reference manual: splinetrials.html , splinetrials.pdf

Downloads:

Package source: splinetrials_0.1.0.tar.gz
Windows binaries: r-devel: splinetrials_0.1.0.zip, r-release: not available, r-oldrel: splinetrials_0.1.0.zip
macOS binaries: r-release (arm64): splinetrials_0.1.0.tgz, r-oldrel (arm64): splinetrials_0.1.0.tgz, r-release (x86_64): splinetrials_0.1.0.tgz, r-oldrel (x86_64): splinetrials_0.1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.