๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

A Mixed-Effects Regression Model for Longitudinal Multivariate Ordinal Data

โœ Scribed by Li C. Liu; Donald Hedeker


Book ID
109223362
Publisher
John Wiley and Sons
Year
2005
Tongue
English
Weight
346 KB
Volume
62
Category
Article
ISSN
0006-341X

No coin nor oath required. For personal study only.


๐Ÿ“œ SIMILAR VOLUMES


A regression model for multivariate rand
โœ Huiman X. Barnhart; Andrzej S. Kosinski; Allan R. Sampson ๐Ÿ“‚ Article ๐Ÿ“… 1999 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 109 KB ๐Ÿ‘ 2 views

Multivariate random length data occur when we observe multiple measurements of a quantitative variable and the variable number of these measurements is also an observed outcome for each experimental unit. For example, for a patient with coronary artery disease, we may observe a number of lesions in

Marginalized transition random effect mo
โœ Ozlem Ilk; Michael J. Daniels ๐Ÿ“‚ Article ๐Ÿ“… 2007 ๐Ÿ› John Wiley and Sons ๐ŸŒ French โš– 223 KB ๐Ÿ‘ 2 views

## Abstract Generalized linear models with random effects and/or serial dependence are commonly used to analyze longitudinal data. However, the computation and interpretation of marginal covariate effects can be difficult. This led Heagerty (1999, 2002) to propose models for longitudinal binary dat

A robust mixed linear model analysis for
โœ Paramjit S. Gill ๐Ÿ“‚ Article ๐Ÿ“… 2000 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 124 KB ๐Ÿ‘ 3 views

This paper describes robust procedures for estimating parameters of a mixed e!ects linear model as applied to longitudinal data. In addition to "xed regression parameters, the model incorporates random subject e!ects to accommodate between-subjects variability and autocorrelation for within-subject