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Stepwise covariate modeling (SCM) for nonlinear mixed-effects models fitted with 'nlmixr2'. Forward inclusion and backward elimination are driven by likelihood-ratio tests, and the covariate terms are generated inside the model body, so continuous covariates are centered and categorical covariates expanded into indicator columns without editing the model by hand. Candidate fits can be cached and resumed, fitted in parallel, and reviewed through per-step and all-candidate summary tables. The approach follows Jonsson and Karlsson (1998) <doi:10.1023/A:1011970125687>, and the implementation in 'Perl-speaks-NONMEM' described by Lindbom, Ribbing and Jonsson (2004) <doi:10.1016/j.cmpb.2003.11.003>.
| Version: | 0.4.1 |
| Depends: | R (≥ 4.1) |
| Imports: | checkmate, cli (≥ 3.4.0), data.table, lotri, nlme, nlmixr2est (≥ 7.0.0), nlmixr2utils (≥ 0.3), rxode2 (≥ 5.0.0), stats, tools, utils |
| Suggests: | future, knitr, nlmixr2data, pkgload, rmarkdown, testthat (≥ 3.0.0), withr |
| Published: | 2026-09-30 |
| DOI: | 10.32614/CRAN.package.nlmixr2scm |
| Author: | Justin Wilkins |
| Maintainer: | Justin Wilkins <justin.wilkins at occams.com> |
| BugReports: | https://github.com/nlmixr2/nlmixr2scm/issues |
| License: | GPL (≥ 3) |
| URL: | https://github.com/nlmixr2/nlmixr2scm |
| NeedsCompilation: | no |
| Materials: | README, NEWS |
| CRAN checks: | nlmixr2scm results |
| Reference manual: | nlmixr2scm.html , nlmixr2scm.pdf |
| Vignettes: |
Stepwise Covariate Modelling with runSCM() (source) |
| Package source: | nlmixr2scm_0.4.1.tar.gz |
| Windows binaries: | r-devel: nlmixr2scm_0.4.1.zip, r-release: nlmixr2scm_0.4.zip, r-oldrel: nlmixr2scm_0.4.1.zip |
| macOS binaries: | r-release (arm64): nlmixr2scm_0.4.tgz, r-oldrel (arm64): nlmixr2scm_0.4.tgz, r-release (x86_64): nlmixr2scm_0.4.1.tgz, r-oldrel (x86_64): nlmixr2scm_0.4.1.tgz |
| Old sources: | nlmixr2scm archive |
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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.