Chris Bilder
Department of Statistics
University of Nebraska-Lincoln
Modeling Association between Two or More Categorical Variables that
Allow for Multiple Category Choices
Multiple-response (or pick any/c) categorical variables summarize responses
to survey questions that ask "pick any" or "choose all that apply" from a
set of item responses. The purpose of this presentation is to introduce
extensions to loglinear modeling in order to model the associations between
these variables simultaneously across all their items. Because individual
item responses to a multiple-response categorical variable are likely to be
correlated, the usual chi-square approximations to model comparison
statistics are not appropriate. A new bootstrap procedure is proposed to
approximate the distribution of these statistics. Asymptotic chi-square
distributional approximations are also developed. Odds ratio and
standardized Pearson residual measures are given to estimate specific
associations and examine deviations from a specified model.
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