A mixed-effect model for positive responses augmented by zeros

作者：Rodrigues Motta Mariana^*; Galvis Soto Diana Milena; Lachos Victor H; Vilca Filidor; Baltar Valeria Troncoso; Verly Junior Eliseu; Fi**erg Regina Mara; Lobo Marchioni Dirce Maria

来源：Statistics in Medicine, 2015, 34(10): 1761-1778.

DOI：10.1002/sim.6450

• Bayesian inference
• gamma distribution
• log-normal distribution
• mixed models
• random effects
• usual intake
• zero-augmented distributions

In this research article, we propose a class of models for positive and zero responses by means of a zero-augmented mixed regression model. Under this class, we are particularly interested in studying positive responses whose distribution accommodates skewness. At the same time, responses can be zero, and therefore, we justify the use of a zero-augmented mixture model. We model the mean of the positive response in a logarithmic scale and the mixture probability in a logit scale, both as a function of fixed and random effects. Moreover, the random effects link the two random components through their joint distribution and incorporate within-subject correlation because of the repeated measurements and between-subject heterogeneity. A Markov chain Monte Carlo algorithm is tailored to obtain Bayesian posterior distributions of the unknown quantities of interest, and Bayesian case-deletion influence diagnostics based on the q-divergence measure is performed. We apply the proposed method to a dataset from a 24hour dietary recall study conducted in the city of SAo Paulo and present a simulation study to evaluate the performance of the proposed methods.

• 出版日期2015-5-10