Two-part mixed-effects location scale models

Mixed-Effects Location-Scale Models for Conditionally Normally Distributed Repeated-Measures Data

MIXREGLS: A Program for Mixed-Effects Location Scale Analysis.

MIXREGLS is a program which provides estimates for a mixed-effects location scale model assuming a (conditionally) normally-distributed dependent variable. This model can be used for analysis of data in which subjects may be measured at many observations and interest is in modeling the mean and variance structure. In terms of the variance structure, covariates can by specified to have effects o...

Inference in Two-Piece Location-Scale Models with Jeffreys Priors

This paper addresses the use of Jeffreys priors in the context of univariate threeparameter location-scale models, where skewness is introduced by differing scale parameters either side of the location. We focus on various commonly used parameterizations for these models. Jeffreys priors are shown not to allow for posterior inference in the wide and practically relevant class of distributions o...

Modeling between-subject and within-subject variances in ecological momentary assessment data using mixed-effects location scale models.

Ecological momentary assessment and/or experience sampling methods are increasingly used in health studies to study subjective experiences within changing environmental contexts. In these studies, up to 30 or 40 observations are often obtained for each subject. Because there are so many measurements per subject, one can characterize a subject's mean and variance and can specify models for both....

Functional mixed effects models.

In this article, a new class of functional models in which smoothing splines are used to model fixed effects as well as random effects is introduced. The linear mixed effects models are extended to nonparametric mixed effects models by introducing functional random effects, which are modeled as realizations of zero-mean stochastic processes. The fixed functional effects and the random functiona...