Testing for centre effects in multi-centre survival studies: a Monte Carlo comparison of fixed and random effects tests
✍ Scribed by Per Kragh Andersen; John P. Klein; Mei-Jie Zhang
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 115 KB
- Volume
- 18
- Category
- Article
- ISSN
- 0277-6715
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✦ Synopsis
The problem of testing for a centre e!ect in multi-centre studies following a proportional hazards regression analysis is considered. Two approaches to the problem can be used. One "ts a proportional hazards model with a "xed covariate included for each centre (except one). The need for a centre speci"c adjustment is evaluated using either a score, Wald or likelihood ratio test of the hypothesis that all the centre speci"c e!ects are equal to zero. An alternative approach is to introduce a random e!ect or frailty for each centre into the model. Recently, Commenges and Andersen have proposed a score test for this random e!ects model. By a Monte Carlo study we compare the performance of these two approaches when either the "xed or random e!ects model holds true. The study shows that for moderate samples the "xed e!ects tests have nominal levels much higher than speci"ed, but the random e!ect test performs as expected under the null hypothesis. Under the alternative hypothesis the random e!ect test has good power to detect relatively small "xed or random centre e!ects. Also, if the centre e!ect is ignored the estimator of the main treatment e!ect may be quite biased and is inconsistent. The tests are illustrated on a retrospective multi-centre study of recovery from bone marrow transplantation.