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  "Title": "Unifying Estimation Results with Binary Dependent Variables",
  "Authors@R": "c(\nperson( \"Arne\", \"Henningsen\",\nemail = \"arne.henningsen@gmail.com\",\nrole = c( \"aut\", \"cre\" ),\ncomment = c( ORCID = \"0000-0002-6720-0264\" ) ),\nperson( \"Geraldine\", \"Henningsen\",\nrole = \"aut\",\ncomment = c( ORCID = \"0000-0002-4651-1039\" ) ) )",
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  "Description": "Calculate unified measures that quantify the effect of a\ncovariate on a binary dependent variable (e.g., for\nmeta-analyses). This can be particularly important if the\nestimation results are obtained with different\nmodels/estimators (e.g., linear probability model, logit,\nprobit, ...) and/or with different transformations of the\nexplanatory variable of interest (e.g., linear, quadratic,\ninterval-coded, ...). The calculated unified measures are: (a)\nsemi-elasticities of linear, quadratic, or interval-coded\ncovariates and (b) effects of linear, quadratic,\ninterval-coded, or categorical covariates when a linear or\nquadratic covariate changes between distinct intervals, the\nreference category of a categorical variable or the reference\ninterval of an interval-coded variable needs to be changed, or\nsome categories of a categorical covariate or some intervals of\nan interval-coded covariate need to be grouped together.\nApproximate standard errors of the unified measures are also\ncalculated. All methods that are implemented in this package\nare described in the 'vignette' \"Extracting and Unifying\nSemi-Elasticities and Effect Sizes from Studies with Binary\nDependent Variables\" that is included in this package.",
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  "URL": "https://github.com/arne-henningsen/urbin/",
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        "Linear probability models and articles reporting marginal effects",
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        "Semi-elasticities of interval-coded covariates",
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        "Conclusion",
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        "Derivation of a binary probit model from an ordered probit model",
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