title: 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.
authors.affiliation: Departamento de Matemática, Faculdade de Ciências da Universidade do Porto e Centro de Matemática da Universidade do Porto, Porto, Portugal. argaio@fc.up.pt
authors.forename: A
authors.initials: A
authors.lastname: Rita Gaio
authors.forename: Joaquim Pinto da
authors.initials: JP
authors.lastname: Costa
authors.forename: Ana Cristina
authors.initials: AC
authors.lastname: Santos
authors.forename: Elisabete
authors.initials: E
authors.lastname: Ramos
authors.forename: Carla
authors.initials: C
authors.lastname: Lopes
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015992:Body Mass Index; D016000:Cluster Analysis; D004032:Diet / Q000009:adverse effects / Q000706:statistics & numerical data*; D004194:Disease / Q000209:etiology; D002149:Energy Intake; D005163:Factor Analysis, Statistical; D005247:Feeding Behavior; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D016008:Statistical Distributions; D055815:Young Adult