A refined method for multivariate meta-analysis and meta-regression

Statistics in Medicine

Volumn 33, Issue 4, 2014, Pages 541-554

  Jackson, Daniel ^a   Riley, Richard D ^b  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^b UNIVERSITY OF BIRMINGHAM   (United Kingdom)

Author keywords

Multivariate meta analysis; Multivariate t distribution; Random effects models; Small sample inference

Indexed keywords

ACCURACY; ANALYSIS OF VARIANCE; ANALYTIC METHOD; ARTICLE; CALCULATION; CORRELATION ANALYSIS; INTERMETHOD COMPARISON; META ANALYSIS (TOPIC); META REGRESSION; METHODOLOGY; MULTIVARIATE ANALYSIS; MULTIVARIATE META ANALYSIS; OUTCOME ASSESSMENT; PROCESS OPTIMIZATION; REGRESSION ANALYSIS; SAMPLE SIZE; SIMULATION; UNIVARIATE ANALYSIS;

MULTIVARIATE META-ANALYSIS; MULTIVARIATE T DISTRIBUTION; RANDOM EFFECTS MODELS; SMALL SAMPLE INFERENCE;

CARCINOMA, NON-SMALL-CELL LUNG; COMPUTER SIMULATION; CONFIDENCE INTERVALS; DISEASE-FREE SURVIVAL; DNA-BINDING PROTEINS; ENDONUCLEASES; HUMANS; LUNG NEOPLASMS; META-ANALYSIS AS TOPIC; MODELS, STATISTICAL; MULTIVARIATE ANALYSIS; PERIODONTAL DISEASES; TREATMENT OUTCOME;

EID: 84892485024     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.5957     Document Type: Article

References (29)

1. Berkey CS, Hoaglin DC, Antczak-Bouckoms A, Mosteller F, Colditz GA. Meta-analysis of multiple outcomes by regression with random effects. Statistics in Medicine 1998; 17: 2537-2550.
2. van Houwelingen HC, Arends LR, Stijnen T. Advanced methods in meta-analysis: multivariate approach and meta-regression. Statistics in Medicine 2002; 21: 589-624.
3. Jackson D, Riley R, White IR. Multivariate meta-analysis: potential and promise (with discussion). Statistics in Medicine 2011; 30: 2481-2510.
4. Hartung J, Knapp G. On tests of the overall treatment effect in meta-analysis with normally distributed responses. Statistics in Medicine 2001; 20: 1771-1782.
5. Hartung J, Knapp G. A refined method for the meta-analysis of controlled clinical trials with binary outcome. Statistics in Medicine 2001; 20: 3875-3889.
6. Sidik K, Jonkman JN. A simple confidence interval for meta-analysis. Statistics in Medicine 2002; 21: 3153-3159.
7. Sidik K, Jonkman JN. Authors reply. Statistics in Medicine 2004; 23: 159-162.
8. DerSimonian R, Laird N. Meta-analysis in clinical trials. Controlled Clinical Trials 1986; 7: 177-188.
9. Jackson D, Bowden J. A re-evaluation of the 'quantile approximation method' for random effects meta-analysis. Statistics in Medicine 2009; 2: 338-348.
10. Biggerstaff BJ, Tweedie RL. Incorporating variability in estimates of heterogeneity in the random effects model in meta-analysis. Statistics in Medicine 1997; 16: 753-768.
11. Jackson D, Bowden J, Baker R. Hoes does the DerSimonian and Laird procedure for random effects meta-analysis compare with its more efficient but harder to compute counterparts?Journal of Statistical Planning and Inference 2010; 140: 961-970.
12. Knapp G, Hartung J. Improved tests for a random effects meta-regression with a single covariate. Statistics in Medicine 2003; 22: 2293-2710.
13. Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta-analysis. Statistics in Medicine 2002; 21: 1539-1558.
14. Copas J. Letters to the editor. Statistics in Medicine 2003; 22: 2667-2668.
15. Baker R, Jackson D. Meta-analysis inside and outside particle physics: two traditions that should converge?Research Synthesis Methods 2013; 4: 109-124.
16. White IR. Multivariate random-effects meta-regression: updates to mvmeta. The Stata Journal 2011; 11: 255-270.
17. Jackson D, White IR, Thompson SG. Extending DerSimonian and Laird's methodology to perform multivariate random effects meta-analyses. Statistics in Medicine 2010; 29: 1282-1297.
18. Chen H, Manning AK, Dupuis J. A method of moments estimator for random effect multivariate meta-analysis. Biometrics 2012; 64: 1278-1284.
19. Jackson D, White IR, Riley RD. A matrix based method of moments for fitting the multivariate random effects model for meta-analysis and meta-regression. The Biometrical Journal 2013; 55: 231-245.
20. Ma Y, Mazumdar M. Multivariate meta-analysis: a robust approach based on the theory of U-statistic. Statistics in Medicine 2011; 30: 2911-2929.
21. Nadarajah S, Kotz S. Mathematical properties of the multivariate t distribution. Applicandae Mathematicae 2005; 89: 53-84.
22. Kotz S, Nadarajah S. Multivariate t Distributions and Their Applications. Cambridge University Press: Cambridge, UK, 2004.
23. Genz A, Bretz F, Miwa T, Mi X, Leisch F, Scheipl F, Bornkamp B, Hothorn T. mvtnorm: Multivariate Normal and t Distributions. R package version 0.9-9995.
24. Tong YL. The Multivariate Normal Distribution. Springer-Verlag: New York, USA, 1990.
25. Gupta AK, Nagar DK. Matrix Variate Distributions. Chapman and Hall/CRC: London, UK, 2000.
26. Gasparrini A. mvmeta: multivariate meta-analysis and meta-regression. R package version 0.2.3.
27. Jackson D, White IR, Riley RD. Quantifying the impact of between-study heterogeneity in multivariate meta-analyses. Statistics in Medicine 2012; 31: 3805-3820.
28. Hubner R, Riley RD, Billingham C, Popat S. Excision repair cross-complementation group 1 (ERCC1) status and lung cancer outcomes: a meta-analysis of published studies and recommendations. PLos One 2011; 6(10):e25164.
29. Riley RD. Multivariate meta-analysis: the effect of ignoring within-study correlation. Journal of the Royal Statistical Society, Series A 2009; 172: 789-811.