✦ LIBER ✦

Marginal modelling of multivariate categorical data

✍ Scribed by Geert Molenberghs; Emmanuel Lesaffre

Publisher: John Wiley and Sons
Year: 1999
Tongue: English
Weight: 169 KB
Volume: 18
Category: Article
ISSN: 0277-6715
DOI: 10.1002/(sici)1097-0258(19990915/30)18:17/18<2237::aid-sim252>3.0.co;2-r

No coin nor oath required. For personal study only.

✦ Synopsis

This paper describes likelihood methods of analysis for multivariate categorical data. The joint distribution is speci"ed in terms of marginal mean functions, and pairwise and higher order association measures. For the association, the emphasis is on global odds ratios. The method allows #exible formulation of a broad class of designs, such as repeated measurements, longitudinal studies, interrater agreement and cross-over trials. The proposed model can be used for parameter estimation and hypothesis testing. Simple "tting algorithms are proposed. The method is illustrated using a data example.

📜 SIMILAR VOLUMES

A Multivariate Analysis of Variance of C

A Multivariate Analysis of Variance of Categorical Data

✍ Dr. Ike B. Onukogu 📂 Article 📅 1986 🏛 John Wiley and Sons 🌐 English ⚖ 412 KB 👁 1 views

Obtaining marginal estimates from condit

Obtaining marginal estimates from conditional categorical repeated measurements models with missing data

✍ J. K. Lindsey 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 101 KB 👁 1 views

The most commonly used models for categorical repeated measurement data are log-linear models. Not only are they easy to "t with standard software but they include such useful models as Markov chains and graphical models. However, these are conditional models and one often also requires the marginal

Modelling ordered categorical data: rece

Modelling ordered categorical data: recent advances and future challenges

✍ Alan Agresti 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 142 KB 👁 1 views

This article summarizes recent advances in the modelling of ordered categorical (ordinal) response variables. We begin by reviewing some models for ordinal data introduced in the literature in the past 25 years. We then survey recent extensions of these models and related methodology for special typ

Multivariate spatial models for event da

Multivariate spatial models for event data

✍ Alastair H. Leyland; Ian H. Langford; Jon Rasbash; Harvey Goldstein 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 104 KB 👁 1 views

Multivariate data analysis: quo vadis? :

Multivariate data analysis: quo vadis? : I. Object-oriented data modelling (OODM)

✍ Kim H. Esbensen; Agnar Höskuldsson 📂 Article 📅 2003 🏛 John Wiley and Sons 🌐 English ⚖ 268 KB

Modelling Heterogeneous Dispersion in Ma

Modelling Heterogeneous Dispersion in Marginal Models for Longitudinal Proportional Data

✍ Peter X.-K. Song; Zhenguo Qiu; Ming Tan 📂 Article 📅 2004 🏛 John Wiley and Sons 🌐 English ⚖ 238 KB