Multinomial logit and the Behavioral Risk Factor Surveillance System (2013) | Learn about multinomial logit in R with data from the Behavioral Risk Factor Surveillance System (2013)
2016
This dataset example introduces readers to multinomial logit. This technique allows researchers to evaluate whether a categorical variable with three or more unordered categories is a function of one or more independent variables. The multinomial logit model is most commonly estimated via maximum likelihood estimation (MLE). This example uses a subset of data from the 2013 Behavioral Risk Factor Surveillance System (BRFSS) operated by the U.S. Centers for Disease Control. It presents an analysis of the strenuousness of the exercise activities someone engaged in during the previous 30 days as a function of their gender, age, and whether a respondent reports ever having ever been told they have arthritis or some similar condition. An analysis like this allows researchers to evaluate factors that predict activity levels, which may be useful in designing fitness plans.
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