Package: pwr4exp 1.0.0.9000

Kai Wang

pwr4exp: Power Analysis for Research Experiments

Provides tools for calculating statistical power for experiments analyzed using linear mixed models. It supports standard designs, including randomized block, split-plot, and Latin Square designs, while offering flexibility to accommodate a variety of other complex study designs.

Authors:Kai Wang [aut, cre, cph], Mutian Niu [aut, cph]

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pwr4exp.pdf |pwr4exp.html✨
pwr4exp/json (API)
NEWS

# Install 'pwr4exp' in R:
install.packages('pwr4exp', repos = c('https://an-ethz.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/an-ethz/pwr4exp/issues

Pkgdown site:https://an-ethz.github.io

Datasets:
  • milk - An exemplary dataset of a 4x4 crossover design with 2 squares

On CRAN:

Conda:

5.26 score 3 stars 2 scripts 169 downloads 9 exports 8 dependencies

Last updated 16 days agofrom:db761f23e3. Checks:4 OK, 5 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 17 2025
R-4.5-winOKMar 17 2025
R-4.5-macOKMar 17 2025
R-4.5-linuxOKMar 17 2025
R-4.4-winNOTEMar 17 2025
R-4.4-macNOTEMar 17 2025
R-4.4-linuxNOTEMar 17 2025
R-4.3-winNOTEMar 17 2025
R-4.3-macNOTEMar 17 2025

Exports:designCODdesignCRDdesignLSDdesignRCBDdesignSPDmkdesignpwr.anovapwr.contrastpwr.summary

Dependencies:emmeansestimabilitylatticeMASSMatrixmvtnormnlmenumDeriv

pwr4exp: Power Analysis for Experimental Designs

R Package Version r packageVersion('pwr4exp')

Rendered frompwr4exp.Rmdusingknitr::rmarkdownon Mar 17 2025.

Last update: 2025-03-17
Started: 2024-08-12