An Overview and Recent Developments in the Analysis of Multistate Processes

Statistics in Medicine, vol. 45, pp. e70493

Abstract

Multistate models offer a powerful framework for studying disease processes and can be used to formulate intensity-based and more descriptive marginal regression models. They also represent a natural foundation for the construction of joint models for disease processes and dynamic marker processes, as well as joint models incorporating random censoring and intermittent observation times. This article reviews the ways multistate models can be formed and fitted to life history data. Recent work on pseudo-values and the incorporation of random effects to model dependence on the process history and between-process heterogeneity are also discussed. The software available to facilitate such analyses is listed.

Authors 8

1. Malka Gorfine corresponding

   Tel Aviv University

   Affiliation as printed

   Department of Statistics and Operations Research Tel Aviv University Tel Aviv Israel

2. Richard J. Cook

   University of Waterloo

   Affiliation as printed

   Department of Statistics and Actuarial Science University of Waterloo Waterloo Canada

3. Per Kragh Andersen

   University of Copenhagen

   Affiliation as printed

   Section of Biostatistics University of Copenhagen Copenhagen Denmark

4. Terry M. Therneau

   Mayo Clinic

   Affiliation as printed

   Division of Biomedical Statistics and Informatics Mayo Clinic Rochester New York USA

5. Pierre Joly

   Université de Bordeaux · Inserm · Bordeaux Population Health

   Affiliation as printed

   Inserm, ISPED, Bordeaux Populations Health Research Center University of Bordeaux Bordeaux France

6. Hein Putter Aachen Department of Biomedical Data Sciences Leiden University Medical Center Leiden The Netherlands

   Leiden University Medical Center

   Affiliation as printed

   Department of Biomedical Data Sciences Leiden University Medical Center Leiden the Netherlands

7. Maja Pohar Perme

   University of Ljubljana

   Affiliation as printed

   Department of Biostatistics and Medical Informatics, Medical Faculty University of Ljubljana Ljubljana Slovenia

8. Michał Abrahamowicz

   McGill University

   Affiliation as printed

   Department of Epidemiology, Biostatistics and Occupational Health McGill University Montreal Canada