Introduction to Logistic Regression for Responses with More than Two Categories
The binary logistic regression is a model that is used when the dependent variable is binary. When the dependent variable is a nominal variable with more than two categories, a multinomial logistic regression can be used. When the response categories of the dependent variable are ordered, ordinal logit models can be used. The workshop is intended for people who would like to learn about multinomial logistic regression and would like to apply it in their research. No previous knowledge of multinomial logistic regression is necessary, although knowledge of binary logistic regression is helpful.
The emphasis will be on deciding when multicategory regression is appropriate, the terminology used, and the interpretation of the results. Output from statistical software will be used in explaining how to interpret results.
Fee: None to members of the Cornell community, but registration is required. Since space is limited, early registration is encouraged.
For times and locations of upcoming workshops, please see the Workshop Schedule.
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