Sometimes you wish to model binary outcomes, variables that can have only two possible values: diseased or nondiseased, and so forth. For instance, you want to describe the risk of getting a disease depending on various kinds of exposures. Chapter 8 discusses some simple techniques based on tabulation, but you might also want to model dose-response relationships (where the predictor is a continuous variable) or model the effect of multiple variables simultaneously. It would be very attractive to be able to use the same modelling techniques as for linear models.
KeywordsLogistic Regression Generalize Linear Model Model Check Dispersion Parameter Residual Deviance
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- Altman, D. G. (1991), Practical Statistics for Medical Research, Chapman & Hall, London.Google Scholar