Transcription of Dummy-Variable Regression
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Dummy-Variable Regression
7 Dummy-VariableRegressionOne of the serious limitations of multiple- Regression analysis, as presented in Chapters 5and 6, is that it accommodates only quantitative response and explanatory variables. In thischapter and the next, I will explain how qualitative explanatory variables, calledfactors, can beincorporated into a linear current chapter begins with an explanation of how adummy-variable regressorcan becoded to represent adichotomous( , two-category) factor. I proceed to show how a set of dummyregressors can be employed to represent apolytomous(many-category) factor. I next describehow interactions between quantitative and qualitative explanatory variables can be represented indummy- Regression models and how to summarize models that incorporate interactions. Finally,I explain why it does not make sense to standardize Dummy-Variable and interaction A Dichotomous FactorLet us consider the simplest case: one dichotomous factor and one quantitative explanatoryvariable.
In particular, if the usual assumptions of the regression model hold, then it is desirable to fit the common-slope model by least squares. One way of formulating the common-slope model is Yi = α +βXi +γDi +εi (7.1) where D, called a dummy-variable regressor or an indicator variable, is coded 1 for men and 0 for women: Di = 1 for men 0 for ...
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