Dummy variables vs. category-wise models
L. Nordstr�m and
Özge Öner ()
Authors registered in the RePEc Author Service: Louise Nordström
Journal of Applied Statistics, 2014, vol. 41, issue 2, 233-241
Empirical research frequently involves regression analysis with binary categorical variables, which are traditionally handled through dummy explanatory variables. This paper argues that separate category-wise models may provide a more logical and comprehensive tool for analysing data with binary categories. Exploring different aspects of both methods, we contrast the two with a Monte Carlo simulation and an empirical example to provide a practical insight.
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Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:41:y:2014:i:2:p:233-241
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