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SRMERS: Semi-Parametric Shape-Restricted Fixed/Mixed Effect(s) Regression Spline

Select the most suitable shape to describe the relationship between the exposure and the outcome among increasing, decreasing, convex, and concave shapes (Yin et al. (2021) <doi:10.1007/s13571-020-00246-7>); estimate the direct and indirect effects with prior knowledge on the relationship between the mediator and the outcome with binary exposure (Yin et al. (2024) <doi:10.1007/s13571-024-00336-w>); estimate the direct and indirect effects using linear regression-based approach (VanderWeele (2015, ISBN:9780199325870)).

Version: 0.1.1
Depends: R (≥ 4.4.0)
Imports: splines2, stats, lme4, nloptr, dplyr, MASS, coneproj, Matrix
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2026-01-13
DOI: 10.32614/CRAN.package.SRMERS (may not be active yet)
Author: Qing Yin [aut, cre], Shyamal Das Peddada [aut], Jennifer Joan Adibi [aut], Jong-Hyeon Jeong [aut]
Maintainer: Qing Yin <qiy25 at pitt.edu>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: SRMERS results

Documentation:

Reference manual: SRMERS.html , SRMERS.pdf
Vignettes: SRMERS-intro (source, R code)

Downloads:

Package source: SRMERS_0.1.1.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): SRMERS_0.1.1.tgz, r-oldrel (arm64): SRMERS_0.1.1.tgz, r-release (x86_64): SRMERS_0.1.1.tgz, r-oldrel (x86_64): SRMERS_0.1.1.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.