MultiRR: Bias, Precision, and Power for Multi-Level Random Regressions

Calculates bias, precision, and power for multi-level random regressions. Random regressions are types of hierarchical models in which data are structured in groups and (regression) coefficients can vary by groups. Tools to estimate model performance are designed mostly for scenarios where (regression) coefficients vary at just one level. 'MultiRR' provides simulation and analytical tools (based on 'lme4') to study model performance for random regressions that vary at more than one level (multi-level random regressions), allowing researchers to determine optimal sampling designs.

Version: 1.1
Imports: MASS, lme4
Published: 2015-10-21
DOI: 10.32614/CRAN.package.MultiRR
Author: Yimen G. Araya-Ajoy
Maintainer: Yimen G. Araya-Ajoy <yimencr at>
License: GPL-2
NeedsCompilation: no
CRAN checks: MultiRR results


Reference manual: MultiRR.pdf


Package source: MultiRR_1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): MultiRR_1.1.tgz, r-oldrel (arm64): MultiRR_1.1.tgz, r-release (x86_64): MultiRR_1.1.tgz, r-oldrel (x86_64): MultiRR_1.1.tgz
Old sources: MultiRR archive


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