Meta-analysis of published data using a linear mixed-effects model

Biometrics

Volumn 52, Issue 2, 1996, Pages 536-544

  Stram, Daniel O ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

Effect heterogeneity; Random effects; Structural variances; Variance components

Indexed keywords

REGRESSION ANALYSIS;

CLINICAL TRIAL; EFFECT HETEROGENEITY; LINEAR MIXED-EFFECTS MODEL; META-ANALYSIS; MIXED EFFECTS; RANDOM EFFECTS; RANDOM EFFECTS MODEL; REGRESSION MODELLING; STRUCTURAL VARIANCE; VARIANCE COMPONENTS;

RANDOM PROCESSES;

ARTICLE; DATA ANALYSIS; GENETIC HETEROGENEITY; META ANALYSIS; MODEL; REGRESSION ANALYSIS; STATISTICAL ANALYSIS; STRUCTURE ANALYSIS;

EID: 0030011571     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.2307/2532893     Document Type: Article

References (19)

1. Aptech Systems. (1991) GAUSS Reference Manual. Kent, Washington: Aptech Systems Inc.
2. Anderson, T. W. (1973). Asympotic efficient estimation of covariance matrices with linear structure. Annals of Statistics 1, 135-141.
3. Begg, C. B. and Pilote, L. (1991). A model for incorporating historical controls into a meta-analysis. Biometrics 47, 899-906.
4. Breslow, N. E. and Clayton, D. G. (1993). Approximate inference in generalized linear mixed models. Journal of the American Statistical Association 88, 9-25.
5. Colditz, G. A., Brewer, T. F., Berkey, C. S., Wilson, M. E., Burdick, E., Fineberg, H. V., and Mosteller F. (1994). Efficacy of BCG vaccine in the prevention of tuberculosis, meta-analysis of the published literature. Journal of the American Medical Association 271, 698-702.
6. DerSimonian, R. and Laird, N. (1986). Meta-analysis in clinical trials. Controlled Clinical Trials 7, 177-188.
7. Dixon, W. J. (ed). (1988). BMDP Statistical Software Manual, Volume 2. Berkeley: University of California Press.
8. Epicenter. (1994). Epilog Plus, Statistics Package for Epidemiology and Clinical Trials. Pasadena, California: Epicenter Software.
9. Goldstein, H. (1986). Multilevel mixed linear model analysis using iterative generalized least squares. Biometrika 73, 43-56.
10. Harville, D. A. (1977). Maximum likelihood approaches to variance component estimation and to related problems. Journal of the American Statistical Association 72, 320-338.
11. Jennrich, R. I. and Schluchter, M. D. (1986). Unbalanced repeated-measures models with structured covariance matrices. Biometrics 42, 805-820.
12. Laird, N. and Ware, J. H. (1982). Random-effects models for longitudinal data. Biometrics 38, 963-974.
13. Lindstrom, M. J. and Bates, D. M. (1988). Newton-Raphson algorithms for linear mixed-effects models for repeated measures data. Journal of the American Statistical Association 83, 1014-1022.
14. Rao, P. S. R. S., Kaplan, J., and Cochran, W. G. (1981). Estimators for the one-way random effects model with unequal error variances. Journal of the American Statistical Association 76, 89-97.
15. SAS. (1995). Technical Report P-229, SAS/STAT Software Changes and Enhancements, Release 6-07. Cary, North Carolina: SAS Institute Inc.
16. Strain, D. O. and Lee, J. W. (1994). Variance components testing in the longitudinal mixed effects model. Biometrics 50, 1171-1177.
17. Szatrowski, T. H. (1978). Explict solutions, one iteration convergence, and averaging in the multivariate normal estimation problem for patterned means and covariances. Annals of the Institute of Statistical Mathematics, Part A 30, 81-88.
18. Tori, V., Simon, R., Russek-Cohen, E., Midthune, D., and Friedman, M. (1992). Statistical model to determine the relationship of response and survival in patients with advanced ovarian cancer treated with chemotherapy. Journal of the National Cancer Institute 84, 407-414.
19. Winship, D. A. (1978). Cimetidine in the treatment of duodenal ulcer. Gastroenterology 74, 402-406.