CRAN/E | multifear

multifear

Multiverse Analyses for Conditioning Data

Installation

About

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.

Citation multifear citation info
github.com/AngelosPsy/multifear
Bug report File report

Key Metrics

Version 0.1.3
R ≥ 3.6.3
Published 2023-09-23 379 days ago
Needs compilation? no
License GPL-3
CRAN checks multifear results

Downloads

Yesterday 3 0%
Last 7 days 36 -43%
Last 30 days 234 -18%
Last 90 days 762 +21%
Last 365 days 2.940 +27%

Maintainer

Maintainer

Angelos-Miltiadis Krypotos

Authors

Angelos-Miltiadis Krypotos

aut / cre / cph

Material

README
NEWS
Reference manual
Package source

Vignettes

Explaining how the multifear package works

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

multifear archive

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