Package: powerly 1.8.6
powerly: Sample Size Analysis for Psychological Networks and More
An implementation of the sample size computation method for network models proposed by Constantin et al. (2021) <doi:10.31234/osf.io/j5v7u>. The implementation takes the form of a three-step recursive algorithm designed to find an optimal sample size given a model specification and a performance measure of interest. It starts with a Monte Carlo simulation step for computing the performance measure and a statistic at various sample sizes selected from an initial sample size range. It continues with a monotone curve-fitting step for interpolating the statistic across the entire sample size range. The final step employs stratified bootstrapping to quantify the uncertainty around the fitted curve.
Authors:
powerly_1.8.6.tar.gz
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powerly.pdf |powerly.html✨
powerly/json (API)
NEWS
| # Install 'powerly' in R: |
| install.packages('powerly', repos = c('https://mihaiconstantin.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mihaiconstantin/powerly/issues
network-modelspower-analysispsychologysample-size-calculation
Last updated 2 years agofrom:13d86e13df. Checks:6 OK, 3 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Apr 01 2025 |
| R-4.5-win | NOTE | Apr 01 2025 |
| R-4.5-mac | NOTE | Apr 01 2025 |
| R-4.5-linux | NOTE | Apr 01 2025 |
| R-4.4-win | OK | Apr 01 2025 |
| R-4.4-mac | OK | Apr 01 2025 |
| R-4.4-linux | OK | Apr 01 2025 |
| R-4.3-win | OK | Apr 01 2025 |
| R-4.3-mac | OK | Apr 01 2025 |
Exports:generate_modelpowerlyvalidate
Dependencies:abindbackportsbase64encbitbit64bootbootnetbroombslibcachemcheckmateclassclicliprclustercocorcodetoolscolorspacecorpcorcorrplotcpp11crayondata.tabledigestdoParalleldplyre1071eigenmodelellipseevaluatefansifarverfastmapfdrtoolfontawesomeforcatsforeachforeignFormulafsgdatagenericsggplot2glassoglmnetglueGPArotationgridExtragtablegtoolshavenhighrHmischmshtmlTablehtmltoolshtmlwidgetsigraphIsingFitIsingSamplerisobanditeratorsjomojpegjquerylibjsonliteknitrlabelinglatticelavaanlifecyclelme4magrittrMASSMatrixmemoisemgcvmgmmicemimeminqamitmlmnormtmunsellmvtnormNetworkToolboxnetworktoolsnlmenloptrnnetnnlsnumDerivordinalpanpatchworkpbapplypbivnormpillarpkgconfigplotrixplyrpngpolynomppcorprettyunitsprogressproxypsychpurrrpwrqgraphquadprogR.matlabR.methodsS3R.ooR.utilsR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreadrreformulasreshape2rlangrmarkdownrpartrstudioapisassscalesshapesmacofsnowsplines2stringistringrsurvivaltibbletidyrtidyselecttinytextzdbucminfutf8vctrsviridisviridisLitevroomweightswithrwordcloudxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Generate true model parameters | generate_model |
| Plot the results of a sample size analysis | plot.Method |
| Plot the results of a sample size analysis validation | plot.Validation |
| Perform sample size analysis | powerly |
| Provide a summary of the sample size analysis results | summary.Method |
| Provide a summary of the sample size analysis validation results | summary.Validation |
| Validate a sample size analysis | validate |
