Unifying Estimation Results with Binary Dependent Variables

Calculate unified measures that quantify the effect of a covariate on a binary dependent variable (e.g., for meta-analyses). This can be particularly important if the estimation results are obtained with different models/estimators (e.g., linear probability model, logit, probit, ...) and/or with different transformations of the explanatory variable of interest (e.g., linear, quadratic, interval-coded, ...). The calculated unified measures are: (a) semi-elasticities of linear, quadratic, or interval-coded covariates and (b) effects of linear, quadratic, interval-coded, or categorical covariates when a linear or quadratic covariate changes between distinct intervals, the reference category of a categorical variable or the reference interval of an interval-coded variable needs to be changed, or some categories of a categorical covariate or some intervals of an interval-coded covariate need to be grouped together. Approximate standard errors of the unified measures are also calculated. All methods that are implemented in this package are described in the 'vignette' "Extracting and Unifying Semi-Elasticities and Effect Sizes from Studies with Binary Dependent Variables" that is included in this package.



Please note that only the most significant changes are reported here. A full ChangeLog is available in the log messages of the SVN repository on R-Forge.

CHANGES IN VERSION 0.1-8 (2019-02-21)

  • added a 'vignette'

    CHANGES IN VERSION 0.1-6 (2018-11-03)

  • initial release on CRAN

Reference manual

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0.1-12 by Arne Henningsen, a month ago


Browse source code at https://github.com/cran/urbin

Authors: Arne Henningsen , Geraldine Henningsen

Documentation:   PDF Manual  

GPL (>= 2) license

Suggests sampleSelection, maxLik, mfx, mlogit, MASS, mvProbit, knitr, stargazer

See at CRAN