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.
|Author:||Yimen G. Araya-Ajoy|
|Maintainer:||Yimen G. Araya-Ajoy <yimencr at gmail.com>|
|CRAN checks:||MultiRR results|
|Windows binaries:||r-devel: MultiRR_1.1.zip, r-release: MultiRR_1.1.zip, r-oldrel: MultiRR_1.1.zip|
|OS X Mavericks binaries:||r-release: MultiRR_1.1.tgz, r-oldrel: MultiRR_1.1.tgz|
|Old sources:||MultiRR archive|
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