A restricted mixture model for dietary pattern analysis in small samples

Abstract

Multivariate finite mixture models have been applied to the identification of dietary patterns. These models are known to have many parameters, and consequently large samples are usually required. We present a special case of a multivariate mixture model that reduces the number of parameters to be estimated and seems adequate for small to moderately sized samples. We illustrate our approach with an analysis of Portuguese data from a food-frequency questionnaire and with a simulation study.