multifear: Multiverse Analyses for Conditioning Data

A suite of functions for performing analyses, based on a multiverse approach, for conditioning data. Specifically, given the appropriate data, the functions are able to perform t-tests, analyses of variance, and mixed models for the provided data and return summary statistics and plots. The function is also able to return for all those tests p-values, confidence intervals, and Bayes factors. The methods are described in Lonsdorf, Gerlicher, Klingelhofer-Jens, & Krypotos (2022) <doi:10.1016/j.brat.2022.104072>.

Version:	0.1.3
Depends:	R (≥ 3.6.3)
Imports:	dplyr (≥ 0.8.4), purrr (≥ 0.3.3), stats (≥ 3.6.2), ez (≥ 4.4.0), stringr (≥ 1.4.0), reshape2 (≥ 1.4.3), tibble (≥ 2.1.3), ggplot2 (≥ 3.2.1), effsize (≥ 0.7.8), nlme (≥ 3.1.144), BayesFactor (≥ 0.9.12.4.2), bayestestR (≥ 0.10.0), broom (≥ 0.5.5), effectsize (≥ 0.4.1), esc (≥ 0.5.1), forestplot (≥ 1.10), bootstrap (≥ 2019.6)
Suggests:	gridExtra (≥ 2.3), fastDummies (≥ 1.6.1), vctrs (≥ 0.3.1), tidyselect (≥ 1.0.0), tidyr (≥ 1.0.2), plyr (≥ 1.8.6), ggraph (≥ 2.0.1), testthat (≥ 2.1.0), cowplot (≥ 1.0.0), covr, knitr, rmarkdown
Published:	2023-09-23
Author:	Angelos-Miltiadis Krypotos [aut, cre, cph]
Maintainer:	Angelos-Miltiadis Krypotos <amkrypotos at gmail.com>
BugReports:	https://github.com/AngelosPsy/multifear/issues
License:	GPL-3
URL:	https://github.com/AngelosPsy/multifear
NeedsCompilation:	no
Citation:	multifear citation info
Materials:	README NEWS
CRAN checks:	multifear results

Documentation:

Reference manual:	multifear.pdf
Vignettes:	Explaining how the multifear package works

Downloads:

Package source:	multifear_0.1.3.tar.gz
Windows binaries:	r-devel: multifear_0.1.3.zip, r-release: multifear_0.1.3.zip, r-oldrel: multifear_0.1.3.zip
macOS binaries:	r-release (arm64): multifear_0.1.3.tgz, r-oldrel (arm64): multifear_0.1.3.tgz, r-release (x86_64): multifear_0.1.3.tgz, r-oldrel (x86_64): multifear_0.1.3.tgz
Old sources:	multifear archive

Linking:

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