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Alternative Regression Models: Logistic, Poisson Regression, and the Generalized Linear Model

Throughout the text we have used the ordinary least squares regression (OLS) model. For statistical inference, OLS regression assumes that the residuals from our analysis are both normally distributed and exhibit homoscedasticity (see Section 4.3). But we are sometimes confronted with a dependent variable Y that does not result in our meeting these assumptions. For example, Y may be dichotomous, as when someone is diagnosed with a disease or not, referred to in the epidemiological literature as “case” versus “noncase” (e.g., Fleiss, 1981). Or Y may be in the form of counts of rare outcomes, for example, the number of bizarre behaviors exhibited by ...

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