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Dummy Variables vs. Category-wise Models
Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University.
Jönköping University.
Jönköping University.
2014 (English)In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 41, no 2, 233-241 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2014. Vol. 41, no 2, 233-241 p.
National Category
Probability Theory and Statistics
Research subject
Statistics/Econometrics
Identifiers
URN: urn:nbn:se:lnu:diva-28562DOI: 10.1080/02664763.2013.838665ISI: 000327237200001Scopus ID: 2-s2.0-84889096817OAI: oai:DiVA.org:lnu-28562DiVA: diva2:643512
Available from: 2013-08-27 Created: 2013-08-27 Last updated: 2017-12-06Bibliographically approved

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Holgersson, Thomas

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