Linear mixed-effects model for longitudinal complex data with diversified characteristics

Beta - Binomial and Ordinal Joint Model with Random Effects for Analyzing Mixed Longitudinal Responses

The analysis of discrete mixed responses is an important statistical issue in various sciences. Ordinal and overdispersed binomial variables are discrete. Overdispersed binomial data are a sum of correlated Bernoulli experiments with equal success probabilities. In this paper, a joint model with random effects is proposed for analyzing mixed overdispersed binomial and ordinal longitudinal respo...

A robust mixed linear model analysis for longitudinal data.

This paper describes robust procedures for estimating parameters of a mixed effects linear model as applied to longitudinal data. In addition to fixed regression parameters, the model incorporates random subject effects to accommodate between-subjects variability and autocorrelation for within-subject variability. Robust empirical Bayesian estimation of subject effects is briefly discussed. As ...

Linear Mixed Models for Longitudinal Data

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A Two-stage Linear Mixed-effects/cox Model for Longitudinal Data

State Space Representation of an Autoregressive Linear Mixed Effects Model for the Analysis of Longitudinal Data

Recently, we proposed an autoregressive linear mixed effects model for the analysis of longitudinal data in which the current response is regressed on the previous response, fixed effects, and random effects (Funatogawa et al., Statist. Med. 2007; 26:2113-2130). The model represents profiles approaching random equilibriums. Because intermittent missing is an inherent problem of the autoregressi...