Dummy variables are variables that take the values of only 0 or 1. They may be explanatory or outcome variables; however, the focus of this article is explanatory or independent variable construction and usage. Typically, dummy variables are used in the following applications: time series analysis with seasonality or regime switching; analysis of qualitative data, such as survey responses; categorical representation, and representation of value levels. Target domains may be economic forecasting, bio-medical research, credit scoring, response modeling, and other fields. Dummy variables may serve as inputs in traditional regression methods or new modeling paradigms, such as genetic algorithms, neural networks, or Boolean network models.
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Submitted by antoq on Wed, 01/07/2009 - 07:11.