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Visits since 08-25-2017

1. Hong, C, Riley, R and Chen, Y (2017) Robust variance estimator for Riley method of the multivariate meta-analysis when within-study correlations are unknown, Research Synthesis Methods, (in press).

 

2. Agarwal, R, Bartsch, SM, Kelly, BJ, Prewitt, M, Liu, YL, Chen, Y, and Umscheid, CA. (2017) Newer glycopeptide antibiotics for treatment of complicated skin and soft tissue infections: a systematic review, network meta-analysis and cost analysis, Clinical Microbiology and Infection (in press).

 

3. Huang, J, Liu, YL, Vitale, S, Penning, T, Whitehead, A, Vachani, A, Clapper, M, Muscat, J, Lazarus, P, Scheet, P, Moore, JH and Chen, Y (2017), On meta- and mega-analyses for gene-environment interactions, Genetic Epidemiology 41: 876-886.

 

4. Ma, X, Lian, X, Chu, H, Ibrahim, J, and Chen, Y (2017) A Bayesian hierarchical model for network meta-analysis of diagnostic tests, Biostatistics (in press).

 

5. Ning, J, Chen, Y and Piao, J (2017) Maximum likelihood estimation and EM algorithm of Copas-like selection model for publication bias correction. Biostatistics 18 (3) 495-504.

 

6. Liu, Y, DeSantis, S and Chen, Y (2017) Bayesian mixed treatment comparisons meta-analysis for correlated outcomes subject to reporting bias, Journal of the Royal Statistical Society: Series C (in press).

 

7. Liu, Y, Chen, Y and Scheet, P (2016), A meta-analytic framework for detection of genetic interactions, Genetic Epidemiology, 40 (7), 534 –543.

 

8. Chen, Y, Liu, Y, Chu, H, Lee, M and Schmid, C (2017) A simple and robust method for multivariate meta-analysis of diagnostic test accuracy, Statistics in Medicine, 36, 105-121.

 

9. Chen, Y, Hong, C, Ning, Y and Su, X. (2016) Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach, Statistics in Medicine, 35, 21-40.

 

10. Chahoud, J, Semaan, A, Chen, Y, Cao, M, Rieber, A, Rady, P and Tyring, S. (2016) The Association between Beta-genus Human Papillomavirus and Cutaneous Squamous Cell Carcinoma in Immunocompetent Individuals: a Meta-analysis, JAMA Dermatology, 152(12):1354–1364.

 

11. Chen, Y, Cai, Y, Hong, C, and Jackson, D. (2016) Inference for correlated effect sizes using multiple univariate meta-analyses, Statistics in Medicine, 35(9): 1405-1422.

 

12. Liu, Y, Chen, Y and Chu H. (2015) A unification of models for meta-analysis of diagnostic accuracy studies without a gold standard, Biometrics, 71(2):538–47.

 

13. Chen, Y, Hong, C and Riley, R. (2015) An alternative pseudolikelihood method for multivariate random-effects meta-analysis, Statistics in Medicine 34 (3): 361-380.

 

14. Chen, Y, Liu, Y, Ning, J, Cormier J and Chu H. (2015) A model for combining case-control and cohort studies in systematic reviews of diagnostic tests, Journal of the Royal Statistical Society: Series C, 64(3): 469-489.

 

15. Chen, Y, Liu, Y, Ning, J, Nie, L, Zhu, H and Chu H. (2014) A composite likelihood method for bivariate analysis of sensitivity and specificity in diagnostic reviews, Statistical Methods in Medical Research.

 

16. Chen, Y, Chu, H, Luo, S, Nie L and Chen S. (2014) Bayesian analysis on meta-analysis of case-control studies accounting for within-study correlation, Statistical Methods in Medical Research.

 

17. Chen, Y, Luo, S, Chu, H, Su, X and Nie, L. (2014) An Empirical Bayes Method for Multivariate Metaanalysis with Application in Clinical Trials, Communications in Statistics-Theory and Methods, 43(16), 3536–3551.

 

18. Ma, X, Chen, Y, Cole, S and Chu, H. (2014) A hybrid Bayesian hierarchical model combining cohort and case-control studies for meta-analysis of diagnostic tests: accounting for partial verification bias, Statistical Methods in Medical Research.

 

19. Luo, S, Chen, Y, Su, X and Chu, H. (2014) mmeta: An R package for multivariate meta-analysis. Journal of Statistical Software, 56 (11).

 

20. Chen, Y, Luo, S, Chu, H and Wei, P. (2013) Bayesian inference on risk differences: an application to multivariate meta-analysis of adverse events in clinical trials, Statistics in Biopharmaceutical Research, 5 (2): 142-155.

 

21. Chu, H, Nie, L, Chen, Y, Huang, Y and Sun, W. (2012) Bivariate random effects models for meta-analysis of comparative studies with binary outcomes: methods for the absolute risk difference and relative risk, Statistical Methods in Medical Research, 21 (6): 621–633.

 

 

 

Publications from XMETA Team

Other References

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Cox D, Reid N. A note on pseudolikelihood constructed from marginal densities. Biometrika 2004; 91(3):729–737.

 

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Duval, S. & Tweedie, R., 2000. Trim and fill: a simple funnel‐plot–based method of testing and adjusting for publication bias in meta‐analysis. Biometrics, 56(2), pp. 455-463.

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Ioannidis, J. P., 2005. Why most published research findings are false.. PLos med , 2(8), p. e124.

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Riley R, Abrams K, Sutton A, Lambert P, Thompson J. Bivariate random-effects meta-analysis and the estimation of between-study correlation. BMC Medical Research Methodology 2007; 7(1):3.

 

Riley R, Thompson J, Abrams K. An alternative model for bivariate random-effects meta-analysis when the within-study correlations are unknown. Biostatistics 2008; 9(1):172–186.

 

Riley R, Abrams K, Lambert P, Sutton A, Thompson J. An evaluation of bivariate random-effects meta-analysis for the joint synthesis of two correlated outcomes. Statistics in medicine 2007; 26(1):78–97.

 

Riley R. Multivariate meta-analysis: the effect of ignoring within-study correlation. Journal of the Royal Statistical Society: Series A (Statistics in Society) 2009; 172(4):789–811. 
 

Sterne, J. A., Egger, M. & Smith, G. D., 2001. Investigating and dealing with publication and other biases in meta-analysis.. British Medical Journal , 323(7304), p. 101

Van Houwelingen HC, Arends LR, Stijnen T. Advanced methods in meta-analysis: multivariate approach and meta-regression.Statistics in medicine 2002; 21(4):589–624.

 

Varin C, Reid N, Firth D. An overview of composite likelihood methods. Statistica Sinica 2011; 21(1):5–42.
 

White I. Multivariate random-effects meta-regression: updates to mvmeta. Stata Journal 2011; 11(2):255–270.

 

 

 

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