Empirical evidence about inconsistency among studies in a pair-wise meta-analysis

Research Synthesis Methods

Volumn 7, Issue 4, 2016, Pages 346-370

  Rhodes, Kirsty M ^a   Turner, Rebecca M ^a   Higgins, Julian P T ^b  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^b UNIVERSITY OF BRISTOL   (United Kingdom)

Author keywords

Bayesian analysis; heterogeneity; inconsistency; intervention studies; meta analysis

Indexed keywords

BAYES THEOREM; BIBLIOGRAPHIC DATABASE; BONE NEOPLASMS; EMPIRICAL RESEARCH; HUMAN; LITERATURE; META ANALYSIS (TOPIC); METHODOLOGY; ODDS RATIO; OUTCOME ASSESSMENT; PROCEDURES; REPRODUCIBILITY; RISK; STATISTICAL ANALYSIS; STATISTICAL MODEL; STATISTICS; TREATMENT OUTCOME;

BAYES THEOREM; BONE NEOPLASMS; DATA INTERPRETATION, STATISTICAL; DATABASES, BIBLIOGRAPHIC; EMPIRICAL RESEARCH; HUMANS; META-ANALYSIS AS TOPIC; MODELS, STATISTICAL; ODDS RATIO; OUTCOME ASSESSMENT (HEALTH CARE); REPRODUCIBILITY OF RESULTS; RESEARCH DESIGN; REVIEW LITERATURE AS TOPIC; RISK; STATISTICS AS TOPIC; TREATMENT OUTCOME;

EID: 85003633081     PISSN: None     EISSN: 17592887     Source Type: Journal    
DOI: 10.1002/jrsm.1193     Document Type: Article

References (46)

1. Böhning D, Malzahn U, Dietz E, Schlattmann P, Viwatwongkasem C, Biggeri A 2002. Some general points in estimating heterogeneity variance with the DerSimonian–Laird estimator. Biostatistics 3(4): 445–457.
2. Brockwell SE, Gordon IR 2001. A comparison of statistical methods for meta-analysis. Statistics in Medicine 20: 825–840.
3. Brockwell SE, Gordon IR 2007. A simple method for inference on an overall effect in meta-analysis. Statistics in Medicine 26: 4531–4543.
4. Brooks SP, Gelman A 1998. General methods for monitoring convergence of iterative simulations. Journal of Computational and Graphical Statistics 7: 434–455.
5. Caldwell DM, Welton NJ, Dias S, Ades A 2012. Selecting the best scale for measuring treatment effect in a network meta-analysis: a case study in childhood nocturnal enuresis. Research Synthesis Methods 3: 126–141.
6. Cornell JE, Mulrow CD, Localio R, Stack CB, Meibohm AR, Guallar E, Eliseo G, Goodman SN 2014. Random-effects meta-analysis of inconsistent effects: a time for change. Annals of Internal Medicine 160: 267–270.
7. Davey J, Turner RM, Clarke MJ, Higgins JPT 2011. Characteristics of meta-analyses and their component studies in the Cochrane Database of Systematic Reviews: a cross-subsectional, descriptive analysis. BMC Medical Research Methodology 11: 160.
8. Deeks J 1998. When can odds ratios mislead? British Medical Journal 317: 1155.
9. Deeks J 2002. Issues in the selection of a summary statistic for meta-analysis of clinical trials with binary outcomes. Statistics in Medicine 21: 1575–1600.
10. DerSimonian R, Laird N 1986. Meta-analysis in clinical trials. Controlled Clinical Trials 7: 177–188.
11. Dias S, Welton NJ, Sutton AJ, Ades AE 2013. Evidence synthesis for decision making 5: the baseline natural history model. Medical Decision Making 33(5): 657–670.
12. Dwan K, Gamble C, Williamson PR 2013. Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias – An Updated Review. PLoS ONE 8(7): e66844. DOI:10.1371/journal.pone.0066844.
13. Engels EA, Schmid CH, Terrin N, Olkin I, Lau J 2000. Heterogeneity and statistical significance in meta-analysis: an empirical study of 125 meta-analyses. Statistics in Medicine 19: 1707–1728.
14. Friedrich JO, Adhikari NKJ, Beyene J 2008. The ratio of means method as an alternative to mean differences for analyzing continuous outcome variables in meta-analysis: a simulation study. BMC Medical Research Methodology 8: 32.
15. Hamza TH, Van Houwelingen HC, Stijnen T 2008. The binomial distribution of meta-analysis was preferred to model within-study variability. Journal of Clinical Epidemiology 61: 41–51.
16. Hartung J, Makambi KH 2003. Reducing the number of unjustified significant results in meta-analysis. Communications in Statistics - Simulation and Computation 32: 1179–1190.
17. Higgins JPT, Whitehead A 1996. Borrowing strength from external trials in a meta-analysis. Statistics in Medicine 15: 2733–2749.
18. Higgins JPT, Thompson SG 2002. Quantifying heterogeneity in a meta-analysis. Statistics in Medicine 21: 1539–1558.
19. Higgins JPT, Thompson SG, Spiegelhalter DJ 2009. A re-evaluation of random-effects meta-analysis. Journal of the Royal Statistical Society A 172(1): 137–159.
20. Knapp G, Hartung J 2003. Improved tests for a random effects meta-regression with a single covariate. Statistics in Medicine 22: 2693–2710.
21. Li C, Xia J, Wang J 2009. Risperidone dose for schizophrenia. Cochrane Database of Systematic Reviews (4): CD007474.
22. Lunn DJ, Thomas A, Best N, Spiegelhalter DJ 2000. WinBUGS-A Bayesian modelling framework: concepts, structure, and extensibility. Statistics and Computing 10: 325–337.
23. Mittlböck M, Heinzl H 2006. A simulation study comparing properties of heterogeneity measures in meta-analysis. Statistics in Medicine 25: 4321–4333.
24. Nagele P 2003. Misuse of standard error of the mean (sem) when reporting variability of a sample. a critical evaluation of four anaesthesia journals. British Journal of Anaesthesia 90(4): 514–516.
25. Norton EC, Miller MM, Wang JJ, Coyne K, Kleinman LC 2012. Rank reversal in indirect comparisons. Value in Health 15(8): 1137–1140.
26. Olkin I 1998. Odds ratios revisited. Evidence-Based Medicine 3: 71.
27. Pullenayegum E 2011. An informed reference prior for between-study heterogeneity in meta-analyses of binary outcomes. Statistics in Medicine 30: 3082–3094.
28. Rhodes KM, Turner RM, Higgins JPT 2015. Predictive distributions were developed for the extent of heterogeneity in meta-analyses of continuous outcomes. Journal of Clinical Epidemiology 68(1): 52–60.
29. Roqué i Figuls M, Martinez-Zapata MJ, Scott-Brown M, Alonso-Coello P 2011. Radioisotopes for metastatic bone pain. Cochrane Database of Systematic Reviews (7): CD003347.
30. 2 in assessing heterogeneity may mislead. BMC Medical Research Methodology 8(79):.
31. Sackett DL, Deeks JJ, Altman D 1996. Down with the odds ratios! Evidence-Based Medicine 1: 164–167.
32. Senn S 1998. Odds ratios revisited. Evidence-Based Medicine 3: 71.
33. Sidik K, Jonkman JN 2005. Simple heterogeneity variance estimation for meta-analysis. Journal of the Royal Statistical Society, Series C 54: 367–384.
34. Sidik K, Jonkman JN 2007. A comparison of heterogeneity variance estimators in combining results of studies. Statistics in Medicine 26: 1964–1981.
35. Smith TC, Spiegelhalter DJ, Thomas A 1995. Bayesian approaches to random-effects meta-analysis: a comparative study. Statistics in Medicine 14: 2685–2699.
36. Spiegelhalter DJ, Best NG, Carlin BP, Van der Linde A 2002. Bayesian measures of model complexity and fit (with discussion). Journal of the Royal Statistical Society B 64: 583–640.
37. Spiegelhalter DJ, Abrams KR, Myles JP 2004. Bayesian Approaches to Clinical Trials and Health-Care Evaluation. 1st edn.England: Wiley.
38. Spiegelhalter DJ, Best NG, Carlin BP, Van der Linde A 2014. The deviance information criterion: 12 years on. Journal of the Royal Statistical Society B 76: 485–493.
39. Thompson SG, Smith TC, Sharp SJ 1997. Investigating underlying risk as a source of heterogeneity in meta-analysis. Statistics in Medicine 16: 2741–2758.
40. Turner RM, Spiegelhalter DJ, Smith GCS, Thompson SG 2009. Bias modelling in evidence synthesis. Journal Royal Statistic Society A 172(1): 21–47.
41. Turner RM, Davey J, Clarke MJ, Thompson SG, Higgins JPT 2012. Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews. International Journal of Epidemiology 41(3): 818–827.
42. van Valkenhoef G, Ades AE 2013. Evidence synthesis assumes additivity on the scale of measurement: response to “Rank reversal in indirect comparisons” by Norton et al. Value in Health 16(2): 449–451.
43. Viechtbauer W 2007. Confidence intervals for the amount of heterogeneity in meta-analysis. Statistics in Medicine 26: 37–52.
44. Warn DE, Thompson SG, Spiegelhalter DJ 2002. Bayesian random effects meta-analysis of trials with binary outcomes: methods for the absolute risk difference and relative risk scales. Statistics in Medicine 21: 1601–1623.
45. Welton NJ, Ades AE, Carlin JB, Altman DG, Sterne JAC 2009. Models for potentially biased evidence in meta-analysis using empirically based priors. Journal Royal Statistic Society A 172: 119–136.
46. Wetterslev J, Thorlund K, Brok J, Gluud C 2009. Estimating required information size by quantifying diversity in random-effect model meta-analyses. BMC Medical Research Methodology 9: 86.