Abstract
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.
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Bibliography
Altman, D. G. (1991), Practical Statistics for Medical Research, Chapman & Hall, London.
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© 2008 Springer Science+Business Media, LLC
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Dalgaard, P. (2008). Logistic regression. In: Introductory Statistics with R. Statistics and Computing. Springer, New York, NY. https://doi.org/10.1007/978-0-387-79054-1_13
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DOI: https://doi.org/10.1007/978-0-387-79054-1_13
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