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.


Reference manual

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0.1-6 by Arne Henningsen, 3 months 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

See at CRAN