betaMC: Monte Carlo for Regression Effect Sizes
Generates Monte Carlo confidence intervals
for standardized regression coefficients (beta) and other effect sizes,
including multiple correlation, semipartial correlations,
improvement in R-squared, squared partial correlations,
and differences in standardized regression coefficients,
for models fitted by lm().
'betaMC' combines ideas from Monte Carlo confidence intervals for the indirect effect
(Pesigan and Cheung, 2024 <doi:10.3758/s13428-023-02114-4>)
and the sampling covariance matrix of regression coefficients
(Dudgeon, 2017 <doi:10.1007/s11336-017-9563-z>)
to generate confidence intervals effect sizes in regression.
| Version: |
1.3.4 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
stats |
| Suggests: |
knitr, rmarkdown, testthat, MASS, mice, Amelia, betaDelta, betaSandwich, betaNB |
| Published: |
2026-06-11 |
| DOI: |
10.32614/CRAN.package.betaMC |
| Author: |
Ivan Jacob Agaloos Pesigan
 [aut, cre,
cph] |
| Maintainer: |
Ivan Jacob Agaloos Pesigan <r.jeksterslab at gmail.com> |
| BugReports: |
https://github.com/jeksterslab/betaMC/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/jeksterslab/betaMC,
https://jeksterslab.github.io/betaMC/ |
| NeedsCompilation: |
no |
| Citation: |
betaMC citation info |
| Materials: |
NEWS |
| CRAN checks: |
betaMC results |
Documentation:
Downloads:
Reverse dependencies:
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