Package: powerly
Title: Sample Size Analysis for Psychological Networks and More
Version: 1.10.0
Authors@R: 
    person(given = "Mihai",
           family = "Constantin",
           role = c("aut", "cre"),
           email = "mihai@mihaiconstantin.com",
           comment = c(ORCID = "0000-0002-6460-0107"))
Description: 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.
License: MIT + file LICENSE
URL: https://powerly.dev
BugReports: https://github.com/mihaiconstantin/powerly/issues
Imports: R6, splines2, quadprog, bootnet, qgraph, parabar, ggplot2,
        rlang, mvtnorm, patchwork
Encoding: UTF-8
RoxygenNote: 7.3.2
Collate: 'Basis.R' 'Model.R' 'GgmModel.R' 'Interpolation.R' 'Spline.R'
        'StepThree.R' 'StepTwo.R' 'Statistic.R' 'PowerStatistic.R'
        'StatisticFactory.R' 'ModelFactory.R' 'StepOne.R' 'Range.R'
        'Method.R' 'QuadprogSolver.R' 'Solver.R' 'SolverFactory.R'
        'Validation.R' 'constants.R' 'exports.R' 'helpers.R' 'logo.R'
        'methods.R' 'powerly-package.R'
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2025-09-01 15:11:31 UTC; mihai
Author: Mihai Constantin [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-6460-0107>)
Maintainer: Mihai Constantin <mihai@mihaiconstantin.com>
Repository: CRAN
Date/Publication: 2025-09-01 15:40:02 UTC
Built: R 4.7.0; ; 2026-05-29 05:29:31 UTC; windows
