Package: powerly 1.10.0
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. (2023) <doi:10.1037/met0000555>. 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_1.10.0.tar.gz
powerly_1.10.0.zip(r-4.7)powerly_1.10.0.zip(r-4.6)powerly_1.10.0.zip(r-4.5)
powerly_1.10.0.tgz(r-4.6-any)powerly_1.10.0.tgz(r-4.5-any)
powerly_1.10.0.tar.gz(r-4.7-any)powerly_1.10.0.tar.gz(r-4.6-any)
powerly_1.10.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
powerly/json (API)
| # 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 from:3fa9e5dc3f. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 205 | ||
| source / vignettes | OK | 240 | ||
| linux-release-x86_64 | OK | 289 | ||
| macos-release-arm64 | OK | 226 | ||
| macos-oldrel-arm64 | OK | 196 | ||
| windows-devel | OK | 179 | ||
| windows-release | OK | 210 | ||
| windows-oldrel | OK | 184 | ||
| wasm-release | OK | 186 |
Exports:generate_modelpowerlyvalidate
Dependencies:abindbackportsbase64encbitbit64bootbootnetbroombslibcachemcallrcheckmateclassclicliprclustercocorcodetoolscolorspacecorpcorcorrplotcpp11crayondata.tabledigestdoParalleldplyre1071eigenmodelellipseevaluatefarverfastmapfdrtoolfilelockfontawesomeforcatsforeachforeignFormulafsgdatagenericsggplot2glassoglassoFastglmnetglueGPArotationgridExtragtablegtoolshavenhighrHmischmshtmlTablehtmltoolshtmlwidgetsigraphIsingFitIsingSamplerisobanditeratorsjomojpegjquerylibjsonliteknitrlabelinglatticelavaanlifecyclelme4magrittrmantarMASSmathjaxrMatrixmemoisemgmmicemimeminqamitmlmnormtmvtnormNetworkToolboxnetworktoolsnlmenloptrnnetnnlsnumDerivordinalotelpanparabarpatchworkpbapplypbivnormpillarpkgconfigplotrixplyrpngpolynomppcorprettyunitsprocessxprogressproxypspsychpurrrpwrqgraphquadprogR.matlabR.methodsS3R.ooR.utilsR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreadrreformulasreshape2rlangrmarkdownrpartrstudioapiS7sassscalesshapesmacofsnowsplines2stringistringrsurvivaltibbletidyrtidyselecttinytextzdbucminfutf8vctrsviridisLitevroomweightswithrwordcloudxfunyaml
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 |
