Bayesian analysis on meta-analysis of case-control studies accounting for within-study correlation

Statistical Methods in Medical Research

Volumn 24, Issue 6, 2015, Pages 836-855

  Chen, Yong ^a   Chu, Haitao ^b   Luo, Sheng ^a   Nie, Lei ^c   Chen, Sining ^d  

^a UNIVERSITY OF TEXAS   (United States)

^b UNIVERSITY OF MINNESOTA   (United States)

^c CENTER FOR DRUG EVALUATION AND RESEARCH   (United States)

^d LUCENT TECHNOLOGIES   (United States)

Author keywords

bivariate beta binomial model; exact method; hypergeometric function; meta analysis; odds ratio; Sarmanov family

Indexed keywords

ARYLAMINE ACETYLTRANSFERASE; NAT2 PROTEIN, HUMAN;

ARTICLE; BAYES THEOREM; CALCULATION; CANCER RISK; CASE CONTROL STUDY; COLORECTAL CANCER; CORRELATIONAL STUDY; HERITABILITY; HUMAN; MATHEMATICAL COMPUTING; PROTEIN ACETYLATION; REGRESSION ANALYSIS; SIMULATION; STATISTICAL DISTRIBUTION; COLORECTAL TUMOR; GENETIC PREDISPOSITION; GENETICS; META ANALYSIS (TOPIC); ODDS RATIO; PROCEDURES; SPACE FLIGHT; STATISTICS; TWIN STUDY;

ARYLAMINE N-ACETYLTRANSFERASE; BAYES THEOREM; CASE-CONTROL STUDIES; COLORECTAL NEOPLASMS; GENETIC PREDISPOSITION TO DISEASE; HUMANS; META-ANALYSIS AS TOPIC; ODDS RATIO; REGRESSION ANALYSIS; SPACE SIMULATION; STATISTICS AS TOPIC; TWIN STUDIES AS TOPIC;

EID: 84893453666     PISSN: 09622802     EISSN: 14770334     Source Type: Journal    
DOI: 10.1177/0962280211430889     Document Type: Article

References (51)

1. Brown LD, Cai TT, DasGupta A,. Interval estimation for a binomial proportion. Stat Sci 2001; 16 (2): 101-133.
2. Haldane BJBS,. The estimation and significance of the logarithm of a ratio of frequencies. Ann Human Genet 1955; 20 (4): 309-311.
3. Anscombe F,. On estimating binomial response relations. Biometrika 1956; 43 (3-4): 461.
4. Agresti A,. On logit confidence intervals for the odds ratio with small samples. Biometrics 1999; 55 (2): 597-602.
5. Sweeting MJ, Sutton AJ, Lambert PC,. What to add to nothing? Use and avoidance of continuity corrections in meta-analysis of sparse data. Stat Med 2004; 23 (9): 1351-1375.
6. Fisher RA,. The logic of inductive inference. J R Stat Soc 1935; 98 (1): 39-82.
7. Cornfield J, Neyman J,. A statistical problem arising from retrospective studies. In: Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability, Berkeley, CA: University of California Press, 1956, pp. 135-148.
8. Liddell D,. Practical tests of 2× 2 contingency tables. The Statistician 1976; 25 (4): 295-304.
9. Berkson J,. In dispraise of the exact test:: Do the marginal totals of the 2X2 table contain relevant information respecting the table proportions? J Stat Plan Inferen 1978; 2 (1): 27-42.
10. D'Agostino RB, Chase W, Belanger A,. The appropriateness of some common procedures for testing the equality of two independent binomial populations. Amer Statist 1988; 42 (3): 198-202.
11. Cornfield J,. A method of estimating comparative rates from clinical data; applications to cancer of the lung, breast, and cervix. J Nat Cancer Inst 1951; 11 (6): 1269.
12. Baptista J, Pike M,. Exact two-sided confidence limits for the odds ratio in a 2 x 2 table. Appl Stat 1977; 26: 214-220.
13. Agresti A, Min Y,. On small-sample confidence intervals for parameters in discrete distributions. Biometrics 2001; 57 (3): 963-971.
14. Aitkin M, Anderson D, Francis B, Hinde J,. Statistical Modelling in GLIM, Oxford: Clarendon Press, 1989.
15. Agresti A, Min Y,. Unconditional small-sample confidence intervals for the odds ratio. Biostatistics 2002; 3 (3): 379.
16. Agresti A, Min Y,. Frequentist performance of Bayesian confidence intervals for comparing proportions in 2× 2 contingency tables. Biometrics 2005; 61 (2): 515-523.
17. Zelen M, Parker R,. Case-control studies and Bayesian inference. Stat Med 1986; 5 (3): 261-269.
18. Ashby D, Hutton JL, McGee MA,. Simple Bayesian analyses for case-control studies in cancer epidemiology. The Statistician 1993; 42 (4): 385-397.
19. Nurminen M, Mutanen P,. Exact Bayesian analysis of two proportions. Scand J Stat 1987; 14 (1): 67-77.
20. Marshall R,. Bayesian analysis of case-control studies. Stat Med 1988; 7 (12): 1223-1230.
21. Ye Z, Parry J,. Meta-analysis of 20 case-control studies on the N-acetyltransferase 2 acetylation status and colorectal cancer risk. Med Sci Monit 2002; 8: CR558-CR565.
22. Sarmanov O,. Generalized normal correlation and two-dimensional Fréchet classes. Soviet Math-Doklady 1966; 7: 596-599.
23. Rothman K, Greenland S, Lash T,. Modern epidemiology, 3rd edition. Philadelphia: Lippincott Williams & Wilkins, 2008.
24. Danaher PJ, Hardie BGS,. Bacon with your eggs? Applications of a new bivariate beta-binomial distribution. The American Statistician 2005; 59 (4): 282-286.
25. Gauss CF,. Disquisitiones generales circa seriem infinitam. Comm Gott 1813; 2: 123-161.
26. Lee MLT,. Properties and applications of the Sarmanov family of bivariate distributions. Commun Stat Theory Methods 1996; 25 (6): 1207-1222.
27. 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. Stat Med 2007; 26 (1): 78-97.
28. Riley RD, Thompson JR, Abrams KR,. An alternative model for bivariate random-effects meta-analysis when the within-study correlations are unknown. Biostatistics 2008; 9 (1): 172.
29. Jackson D, White IR, Thompson SG,. Extending DerSimonian and Laird's methodology to perform multivariate random effects meta-analyses. Stat Med 2010; 29 (12): 1282-1297.
30. Cole BF, Lee MLT, Whitmore GA, Zaslavsky AM,. An empirical Bayes model for Markov-dependent binary sequences with randomly missing observations. J Am Stat Assoc 1995; 90 (432): 1364-1372.
31. Shubina M, Lee MLT,. On maximum attainable correlation and other measures of dependence for the Sarmanov family of bivariate distributions. Commun Stat Theory Methods 2004; 33 (5): 1031-1052.
32. Farlie D,. The performance of some correlation coefficients for a general bivariate distribution. Biometrika 1960; 47 (3-4): 307.
33. Efron B, Morris C,. Stein's estimation rule and its competitors-an empirical Bayes approach. J Am Stat Assoc 1973; 68 (341): 117-130.
34. Efron B, Morris C,. Data analysis using Stein's estimator and its generalizations. J Am Stat Assoc 1975; 70 (350): 311-319.
35. Gelman A, Carlin J, Stern H, Rubin D,. Bayesian data analysis, Boca Raton, FL: CRC press, 2004.
36. Carlin BP, Louis TA,. Bayesian methods for data analysis, Chapman & Hall/CRC, 2009.
37. Deely J, Lindley D,. Bayes empirical Bayes. Journal Am Stat Assoc 1981; 76 (376): 833-841.
38. Carlin BP, Gelfand AE,. A sample reuse method for accurate parametric empirical Bayes confidence intervals. J R Stat Soc B (Methodological) 1991; 53 (1): 189-200.
39. Kass RE, Raftery AE,. Bayes factors. J Am Stat Assoc 1995; 90 (430): 773-795.
40. Howard J,. The 2x2 table: a discussion from a Bayesian viewpoint. Stat Sci 1998; 13 (4): 351-367.
41. Ladero JM, González JF, Benítez J, Vargas E, Fernández MJ, Baki W, et al. Acetylator polymorphism in human colorectal carcinoma. Cancer Res 1991; 51 (8): 2098.
42. Chen J, Stampfer MJ, Hough HL, Garcia-Closas M, Willett WC, Hennekens CH, et al. A prospective study of N-acetyltransferase genotype, red meat intake, and risk of colorectal cancer. Cancer Res 1998; 58 (15): 3307.
43. Yoshioka M, Katoh T, Nakano M, Takasawa S, Nagata N, Itoh H,. Glutathione S-transferase (GST) M1, T1, P1, N-acetyltransferase (NAT) 1 and 2 genetic polymorphisms and susceptibility to colorectal cancer. J UOEH 1999; 21 (2): 133.
44. Butler WJ, Ryan P, Roberts-Thomson IC,. Metabolic genotypes and risk for colorectal cancer. J Gastroenterol Hepatol 2001; 16 (6): 631-635.
45. DerSimonian R, Laird N,. Meta-analysis in clinical trials∗ 1. Controlled Clin Trials 1986; 7 (3): 177-188.
46. Cantor RM, Lange K, Sinsheimer JS,. Prioritizing GWAS results: a review of statistical methods and recommendations for their application. Am J Human Genet 2010; 86 (1): 6-22.
47. Zeggini E, Ioannidis JPA,. Meta-analysis in genome-wide association studies. Pharmacogenomics 2009; 10 (2): 191-201.
48. Van Houwelingen HC, Zwinderman KH, Stijnen T,. A bivariate approach to meta-analysis. Stat Med 1993; 12 (24): 2273-2284.
49. Smith TC, Spiegelhalter DJ, Thomas A,. Bayesian approaches to random-effects meta-analysis: A comparative study. Statistics in Medicine 1995; 14 (24): 2685-2699.
50. Skrondal A, Rabe-Hesketh S,. Generalized latent variable modeling: multilevel, longitudinal, and structural equation models, Boca Raton, FL: CRC Press, 2004.
51. Chu H, Cole SR,. Bivariate meta-analysis of sensitivity and specificity with sparse data: a generalized linear mixed model approach. J Clin Epidemiol 2006; 59 (12): 1331.