Package: MultiRR 1.1

Yimen G. Araya-Ajoy

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-4.5-any)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)

# Install 'MultiRR' in R:
install.packages('MultiRR', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues

On CRAN:

archivedpackagesr-universe

1.70 score 5 stars 176 downloads 13 exports 13 dependencies

Last updated 25 days agofrom:b89612e34c (on package/MultiRR). Checks:8 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKJan 26 2025
R-4.5-winOKJan 26 2025
R-4.5-macOKJan 26 2025
R-4.5-linuxOKJan 26 2025
R-4.4-winOKJan 26 2025
R-4.4-macOKJan 26 2025
R-4.3-winOKJan 26 2025
R-4.3-macOKJan 26 2025

Exports:Anal.MultiRRBiasImprecisionlmerAlllower2mean2median2Plot.SimPowersd2Sim.MultiRRSummaryupper2

Dependencies:bootlatticelme4MASSMatrixminqanlmenloptrrbibutilsRcppRcppEigenRdpackreformulas