# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "betaMC" in publications use:' type: software license: MIT title: 'betaMC: Monte Carlo for Regression Effect Sizes' version: 1.3.2.9000 doi: 10.3758/s13428-023-02114-4 identifiers: - type: doi value: 10.32614/CRAN.package.betaMC abstract: 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, 2023 ) and the sampling covariance matrix of regression coefficients (Dudgeon, 2017 ) to generate confidence intervals effect sizes in regression. authors: - family-names: Pesigan given-names: Ivan Jacob Agaloos email: r.jeksterslab@gmail.com orcid: https://orcid.org/0000-0003-4818-8420 preferred-citation: type: article title: Monte Carlo confidence intervals for the indirect effect with missing data authors: - family-names: Pesigan given-names: Ivan Jacob Agaloos email: r.jeksterslab@gmail.com orcid: https://orcid.org/0000-0003-4818-8420 - family-names: Cheung given-names: Shu Fai email: shufai.cheung@gmail.com orcid: https://orcid.org/0000-0002-9871-9448 year: '2023' doi: 10.3758/s13428-023-02114-4 journal: Behavior Research Methods repository: https://jeksterslab.r-universe.dev repository-code: https://github.com/jeksterslab/betaMC commit: bbdcf4938d2b44f2ddc86142622b8e7ea1b9f384 url: https://jeksterslab.github.io/betaMC/ contact: - family-names: Pesigan given-names: Ivan Jacob Agaloos email: r.jeksterslab@gmail.com orcid: https://orcid.org/0000-0003-4818-8420