Multinomial Regression for Outcome Categories (55 Patients)

  • Cleophas T
  • Zwinderman A
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Abstract

In clinical research it is not uncommon that outcome variables are categorical, e.g., the choice of food, treatment modality, type of doctor etc. If such outcome variables are binary, then binary logistic regression is appropriate (Chaps. 36, 37, 38, 39). If, however, we have three or more alternatives, then multinomial logistic regression must be used. It works, essentially, similarly to the recoding procedure reviewed in Chap. 8 on categorical predictors variables. Multinomial logistic regression should not be confounded with ordered logistic regression, which is used in case the outcome variable consists of categories, that can be ordered in a meaningful way, e.g., anginal class or quality of life class (Chap. 48).

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Cleophas, T. J., & Zwinderman, A. H. (2016). Multinomial Regression for Outcome Categories (55 Patients). In SPSS for Starters and 2nd Levelers (pp. 253–257). Springer International Publishing. https://doi.org/10.1007/978-3-319-20600-4_44

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