Package: pwr4exp 0.1.0.9000

Kai Wang

pwr4exp: Power Analysis for Research Experiments

Provides tools for calculating statistical power and determining sample size for a variety of experimental designs used in agricultural and biological research, including completely randomized, block, and split-plot designs. Supports customized designs and allows specification of main effects, interactions, and contrasts for accurate power analysis.

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

Datasets:

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

On CRAN:

4.95 score 3 stars 2 scripts 230 downloads 9 exports 64 dependencies

Last updated 1 months agofrom:87fb13524d. Checks:OK: 7. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 11 2024
R-4.5-win	OK	Nov 11 2024
R-4.5-linux	OK	Nov 11 2024
R-4.4-win	OK	Nov 11 2024
R-4.4-mac	OK	Nov 11 2024
R-4.3-win	OK	Nov 11 2024
R-4.3-mac	OK	Nov 11 2024

Exports:designCOD designCRD designCustom designLSD designRCBD designSPD find_sample_size pwr.anova pwr.contrast

Dependencies:abind backports boot broom car carData cli colorspace cowplot cpp11 Deriv doBy dplyr emmeans estimability fansi farver Formula generics ggplot2 glue gtable isoband labeling lattice lifecycle lme4 lmerTest magrittr MASS Matrix MatrixModels mgcv microbenchmark minqa modelr munsell mvtnorm nlme nloptr nnet numDeriv pbkrtest pillar pkgconfig purrr quantreg R6 RColorBrewer Rcpp RcppEigen rlang scales SparseM stringi stringr survival tibble tidyr tidyselect utf8 vctrs viridisLite withr

pwr4exp: Power Analysis for Experimental Designs

Rendered frompwr4exp.Rmdusingknitr::rmarkdownon Nov 11 2024.

Last update: 2024-10-06
Started: 2024-08-12

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Calculate variance covariance parameters	calc.theta
Extend lmerModLmerTest class	customLmerMod-class
Creation of Experimental Designs	design.COD design.CRD design.Custom design.LSD design.RCBD design.SPD designCOD designCRD designCustom designLSD designRCBD designSPD
Create a data frame for Crossover design	df.cod
Create a data frame of completely randomized design	df.crd
Create a data frame for Latin square design	df.lsd
Create a data frame of randomized complete block design	df.rcbd
Create data frame for split-plot design	df.spd
Determine the sample size required to achieve the target power	find_sample_size
Create an artificial model object	fit.pseu.model
An exemplary dataset of a 4x4 crossover design with 2 squares	milk
Power of omnibus test	pwr.anova
Power of contrasts	pwr.contrast
Naming theta Naming the vector in the order of model specification and in the actual order used in the model	theta.names