Random-Effects Meta-Analysis of Time-to-Event Data Using the Expectation-Maximisation Algorithm and Shrinkage Estimators

Autor/inn/en	Simmonds, Mark C.; Higgins, Julian P. T.; Stewart, Lesley A.
Titel	Random-Effects Meta-Analysis of Time-to-Event Data Using the Expectation-Maximisation Algorithm and Shrinkage Estimators
Quelle	In: Research Synthesis Methods, 4 (2013) 2, S.144-155 (12 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1759-2879
DOI	10.1002/jrsm.1067
Schlagwörter	Meta Analysis; Markov Processes; Monte Carlo Methods; Statistics; Expectation; Patients; Robustness (Statistics); Mathematics; Data + Suchen Sie Ihr Suchwort? Meta-analysis; Metaanalyse; Markowscher Prozess; Monte-Carlo-Methode; Statistik; Expectancy; Erwartung; Patient; Widerstandsfähigkeit; Mathematik; Daten
Abstract	Meta-analysis of time-to-event data has proved difficult in the past because consistent summary statistics often cannot be extracted from published results. The use of individual patient data allows for the re-analysis of each study in a consistent fashion and thus makes meta-analysis of time-to-event data feasible. Time-to-event data can be analysed using proportional hazards models, but incorporating random effects into these models is not straightforward in standard software. This paper fits random-effects proportional hazards models by treating the random effects as missing data and applying the expectation-maximisation algorithm. This approach has been used before by using Markov chain Monte Carlo methods to perform the expectation step of the algorithm. In this paper, the expectation step is simplified, without sacrificing accuracy, by approximating the expected values of the random effects using simple shrinkage estimators. This provides a robust method for fitting random-effects models that can be implemented in standard statistical packages. (As Provided).
Anmerkungen	Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01