Faculty Collaboration Database

Testing for centre effects in multi-centre survival studies: a Monte Carlo comparison of fixed and random effects tests. Stat Med 1999 Jun 30;18(12):1489-500

Date

07/09/1999

Pubmed ID

10398287

DOI

10.1002/(sici)1097-0258(19990630)18:12<1489::aid-sim140>3.0.co;2-#

Scopus ID

2-s2.0-0033618142 (requires institutional sign-in at Scopus site)   196 Citations

Abstract

The problem of testing for a centre effect in multi-centre studies following a proportional hazards regression analysis is considered. Two approaches to the problem can be used. One fits a proportional hazards model with a fixed covariate included for each centre (except one). The need for a centre specific adjustment is evaluated using either a score, Wald or likelihood ratio test of the hypothesis that all the centre specific effects are equal to zero. An alternative approach is to introduce a random effect or frailty for each centre into the model. Recently, Commenges and Andersen have proposed a score test for this random effects model. By a Monte Carlo study we compare the performance of these two approaches when either the fixed or random effects model holds true. The study shows that for moderate samples the fixed effects tests have nominal levels much higher than specified, but the random effect test performs as expected under the null hypothesis. Under the alternative hypothesis the random effect test has good power to detect relatively small fixed or random centre effects. Also, if the centre effect is ignored the estimator of the main treatment effect may be quite biased and is inconsistent. The tests are illustrated on a retrospective multi-centre study of recovery from bone marrow transplantation.

Author List

Andersen PK, Klein JP, Zhang MJ

Author

Mei-Jie Zhang PhD Professor in the Institute for Health and Equity department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Bone Marrow Transplantation
Clinical Trials as Topic
Computer Simulation
Humans
Leukemia, Myeloid, Acute
Monte Carlo Method
Multicenter Studies as Topic
Proportional Hazards Models
Prospective Studies
Retrospective Studies