Package: MultiRR 1.1

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.

Authors:Yimen G. Araya-Ajoy

MultiRR_1.1.tar.gz
MultiRR_1.1.zip(r-4.5)MultiRR_1.1.zip(r-4.4)MultiRR_1.1.zip(r-4.3)
MultiRR_1.1.tgz(r-4.4-any)MultiRR_1.1.tgz(r-4.3-any)
MultiRR_1.1.tar.gz(r-4.5-noble)MultiRR_1.1.tar.gz(r-4.4-noble)
MultiRR_1.1.tgz(r-4.4-emscripten)MultiRR_1.1.tgz(r-4.3-emscripten)
MultiRR.pdf |MultiRR.html✨
MultiRR/json (API)

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

13 exports 0.00 score 10 dependencies 14 scripts 134 downloads

Last updated 9 years agofrom:ce7e057847. Checks:OK: 7. Indexed: yes.

Exports:Anal.MultiRRBiasImprecisionlmerAlllower2mean2median2Plot.SimPowersd2Sim.MultiRRSummaryupper2

Dependencies:bootlatticelme4MASSMatrixminqanlmenloptrRcppRcppEigen