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jeksterslab
betaSandwich:Robust Confidence Intervals for Standardized Regression Coefficients
Generates robust confidence intervals for standardized regression coefficients using heteroskedasticity-consistent standard errors for models fitted by lm() as described in Dudgeon (2017) <doi:10.1007/s11336-017-9563-z>. The package can also be used to generate confidence intervals for R-squared, adjusted R-squared, and differences of standardized regression coefficients. A description of the package and code examples are presented in Pesigan, Sun, and Cheung (2023) <doi:10.1080/00273171.2023.2201277>.
Maintained by Ivan Jacob Agaloos Pesigan. Last updated 2 months ago.
confidence-intervalsheteroskedasticity-consistent-standard-errorsstandardized-regression-coefficients
82.1 match 4.16 score 16 scriptsjeksterslab
betaDelta:Confidence Intervals for Standardized Regression Coefficients
Generates confidence intervals for standardized regression coefficients using delta method standard errors for models fitted by lm() as described in Yuan and Chan (2011) <doi:10.1007/s11336-011-9224-6> and Jones and Waller (2015) <doi:10.1007/s11336-013-9380-y>. The package can also be used to generate confidence intervals for differences of standardized regression coefficients and as a general approach to performing the delta method. A description of the package and code examples are presented in Pesigan, Sun, and Cheung (2023) <doi:10.1080/00273171.2023.2201277>.
Maintained by Ivan Jacob Agaloos Pesigan. Last updated 2 months ago.
confidence-intervalsdelta-method-standard-errorsstandardized-regression-coefficients
66.2 match 4.20 score 20 scriptsjeksterslab
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, 2023 <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.
Maintained by Ivan Jacob Agaloos Pesigan. Last updated 2 months ago.
confidence-intervalsmonte-carloregression-effect-sizesstandardized-regression-coefficients
47.0 match 1 stars 4.27 score 22 scriptsjeksterslab
betaNB:Bootstrap for Regression Effect Sizes
Generates nonparametric bootstrap confidence intervals (Efron and Tibshirani, 1993: <doi:10.1201/9780429246593>) 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().
Maintained by Ivan Jacob Agaloos Pesigan. Last updated 2 months ago.
confidence-intervalsnonparametric-bootstrapregression-effect-sizesstandardized-regression-coefficients
43.6 match 1 stars 4.16 score 18 scripts