The pioneering contributions of G. Glass, the psychologist who invented the term meta-analysis

  • Glass GV. Primary, secondary, and meta-analysis of research. Educational Researcher, 1976; 5: 3-8. [PDF]
  • Glass GV. Meta-analysis at 25. Technical Report, 2000 [HTML]

Two very important tutorials in meta-analysis with emphasis in the statistical methods (Statistics in Medicine)

  • Normand SL. Meta-analysis: formulating, evaluating, combining, and reporting.Stat Med. 1999;18(3):321-59. [PDF]
  • van Houwelingen HC, Arends LR, Stijnen T. Advanced methods in meta-analysis: multivariate approach and meta-regression. Stat Med. 2002;21(4):589-624.[PDF]

A series of tutorials published in BMJ concerning meta-analysis

  • Egger M, Smith GD. Meta-Analysis. Potentials and promise.BMJ. 1997;315(7119):1371-4.[PDF]
  • Egger M, Smith GD, Phillips AN. Meta-analysis: principles and procedures.BMJ. 1997;315(7121):1533-7.[PDF]
  • Davey Smith G, Egger M, Phillips AN. Meta-analysis. Beyond the grand mean? BMJ. 1997; 315(7122):1610-4.[PDF]
  • Egger M, Smith GD. Bias in location and selection of studies.BMJ. 1998; 316(7124):61-6 [PDF]
  • Egger M, Schneider M, Davey Smith G. Spurious precision? Meta-analysis of observational studies.BMJ. 1998; 316(7125):140-4.[PDF]
  • Davey Smith G, Egger M. Meta-analysis. Unresolved issues and future developments.BMJ. 1998; 316(7126): 221-5.[PDF]
  • Altman DG. Systematic reviews of evaluations of prognostic variablesBMJ (Clinical research ed.). 2001;323(7306):224-8. [PDF].
  • S. J. Sharp, S. G. Thompson, D. G. Altman. The relation between treatment benefit and underlying risk in meta-analysis.BMJ. 1996 September 21; 313(7059): 735–738. [PDF]
  • Julian P T Higgins, Simon G Thompson, Jonathan J Deeks, Douglas G Altman. Measuring inconsistency in meta-analyses. BMJ. 2003 September 6; 327(7414): 557–560 [PDF]

Tutorials given by our team

A glossary of terms used in meta-analysis

  • M Delgado-Rodríguez. Glossary on meta-analysis. J. Epidemiol. Community Health, 2001;55;534-536  [PDF]

Special topics in meta-analysis

  • Bagos PG, Nikolopoulos GK. Mixed-effects Poisson regression models for meta-analysis of follow-up studies with constant or varying durations. 2009, The International Journal of Biostatistics, 5(1), Article 21 [PDF]
  • Bagos PG. Meta-analysis in Stata using gllamm. Research Synthesis Methods 2015 [PDF][Pubmed] [Google Scholar]
  • Riley RD, Thompson JR, Abrams KR (2008) An alternative model for bivariate random-effects meta-analysis when the within-study correlations are unknown. Biostatistics 9(1): 172-186 [PDF]
  • Riley RD, Abrams KR, Sutton AJ, Lambert PC, Thompson JR. Bivariate random-effects meta-analysis and the estimation of between-study correlation. BMC Med Res Methodol. 2007 12;7:3. [PDF]
  • Berkey CS, Hoaglin DC, Antczak-Bouckoms A, Mosteller F, Colditz GA (1998) Meta-analysis of multiple outcomes by regression with random effects. Stat Med 17(22): 2537-2550
  • Daniels MJ, Hughes MD (1997) Meta-analysis for the evaluation of potential surrogate markers. Stat Med 16(17): 1965-1982
  • Harbord RM, Deeks JJ, Egger M, Whiting P, Sterne JA (2007) A unification of models for meta-analysis of diagnostic accuracy studies. Biostatistics 8(2): 239-251 [PDF]
  • Higgins JP, Thompson SG (2004) Controlling the risk of spurious findings from meta-regression. Stat Med 23(11): 1663-1682
  • Higgins JP, Whitehead A (1996) Borrowing strength from external trials in a meta-analysis. Stat Med 15(24): 2733-2749
  • Higgins JP, Whitehead A, Turner RM, Omar RZ, Thompson SG (2001) Meta-analysis of continuous outcome data from individual patients. Stat Med 20(15): 2219-2241
  • Lu G, Ades AE (2004) Combination of direct and indirect evidence in mixed treatment comparisons. Stat Med 23(20): 3105-3124
  • Olkin I, Sampson A (1998) Comparison of meta-analysis versus analysis of variance of individual patient data. Biometrics 54(1): 317-322
  • Mathew T, Nordstrom K (1999) On the equivalence of meta-analysis using literature and using individual patient data. Biometrics 55(4): 1221-1223
  • Glenny AM, Altman DG, Song F, Sakarovitch C, Deeks JJ, D'Amico R, Bradburn M, Eastwood AJ; International Stroke Trial Collaborative Group. Indirect comparisons of competing interventions.Health Technol Assess. 2005 Jul;9(26):1-134, iii-iv. [PDF]
  • Thompson SG, Higgins JP (2002) How should meta-regression analyses be undertaken and interpreted? Stat Med 21(11): 1559-1573
  • Thompson SG, Turner RM, Warn DE (2001) Multilevel models for meta-analysis, and their application to absolute risk differences. Stat Methods Med Res 10(6): 375-392
  • Sutton AJ, Abrams KR (2001) Bayesian methods in meta-analysis and evidence synthesis. Stat Methods Med Res 10(4): 277-303
  • Smith TC, Spiegelhalter DJ, Thomas A (1995) Bayesian approaches to random-effects meta-analysis: a comparative study. Stat Med 14(24): 2685-2699
  • Trikalinos TA, Olkin I (2008) A method for the meta-analysis of mutually exclusive binary outcomes. Stat Med
  • Turner RM, Omar RZ, Yang M, Goldstein H, Thompson SG (2000) A multilevel model framework for meta-analysis of clinical trials with binary outcomes. Stat Med 19(24): 3417-3432
  • Whitehead A, Omar RZ, Higgins JP, Savaluny E, Turner RM, Thompson SG (2001) Meta-analysis of ordinal outcomes using individual patient data. Stat Med 20(15): 2243-2260
  • Trikalinos TA, Salanti G, Zintzaras E, Ioannidis JP (2008) Meta-analysis methods. Adv Genet 60: 311-334
  • Shi JQ, Copas JB (2004) Meta-analysis for trend estimation. Stat Med 23(1): 3-19; discussion 159-162
  • Greenland S, Longnecker MP (1992) Methods for trend estimation from summarized dose-response data, with applications to meta-analysis. Am J Epidemiol 135(11): 1301-1309
  • Whitehead A, Whitehead J.A general parametric approach to the meta-analysis of randomized clinical trials.Stat Med. 1991 Nov;10(11):1665-77.
  • Higgins JP, White IR, Wood AM: Imputation methods for missing outcome data in meta-analysis of clinical trials. Clin Trials 2008, 5:225-239. [PDF]
  • Abrams K, Sansó B: Approximate Bayesian inference for random effects meta-analysis. Stat Med 1998, 17:201-218.  [PDF]
  • Peters JL, Mengersen KL: Meta-analysis of repeated measures study designs. J Eval Clin Pract 2008, 14:941-950. 
  • Higgins JPT, White IR, Anzures-Cabrera J: Meta-analysis of skewed data: combining results reported on log-transformed or raw scales. Stat Med 2008, 27:6072-6092. 
  • White IR, Higgins JPT, Wood AM: Allowing for uncertainty due to missing data in meta-analysis--part 1: two-stage methods. Stat Med 2008, 27:711-727.  
  • White IR, Welton NJ, Wood AM, Ades AE, Higgins JPT: Allowing for uncertainty due to missing data in meta-analysis--part 2: hierarchical models. Stat Med 2008, 27:728-745.  [PPT]
  • Di Pietrantonj C: Four-fold table cell frequencies imputation in meta analysis. Stat Med 2006, 25:2299-2322. 
  • Parmar MK, Torri V, Stewart L: Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Stat Med 1998, 17:2815-2834. 
  • Chinn S: A simple method for converting an odds ratio to effect size for use in meta-analysis. Stat Med 2000, 19:3127-3131.
  • Suissa S: Binary methods for continuous outcomes: a parametric alternative. J Clin Epidemiol 1991, 44:241-248.  
  • Chêne G, Thompson SG: Methods for Summarizing the Risk Associations of Quantitative Variables in Epidemiologic Studies in a Consistent Form. American Journal of Epidemiology 1996, 144:610 -621.  [PDF]
  • Smith CT, Williamson PR, Marson AG: Investigating heterogeneity in an individual patient data meta-analysis of time to event outcomes. Stat Med 2005, 24:1307-1319. 
  • Lyman G, Kuderer N: The strengths and limitations of meta-analyses based on aggregate data. BMC Medical Research Methodology 2005, 5:14. [PDF]
  • Tierney JF, Stewart LA, Ghersi D, Burdett S, Sydes MR: Practical methods for incorporating summary time-to-event data into meta-analysis. Trials , 8:16-16. [PDF]
  • Abrams KR, Gillies CL, Lambert PC: Meta-analysis of heterogeneously reported trials assessing change from baseline. Stat Med 2005, 24:3823-3844.
  • Stram DO (1996) Meta-analysis of published data using a linear mixed-effects model. Biometrics 52(2): 536-544
  • Breslow N, Leroux B, Platt R. Approximate hierarchical modelling of discrete data in epidemiology. Stat Methods Med Res 1998, 7(1):49-62.
  • Platt RW, Leroux BG, Breslow N. Generalized linear mixed models for meta-analysis. Stat Med 1999, 18(6):643-654.
  • Thompson SG, Turner RM, Warn DE. Multilevel models for meta-analysis, and their application to absolute risk differences. Stat Methods Med Res 2001, 10(6):375-392.
  • Jackson D, White IR, Thompson SG: Extending DerSimonian and Laird's methodology to perform multivariate random effects meta-analyses. Stat Med 2010, 29:1282-1297.  [PPT]
  • Lau J, Schmid CH, Chalmers TC. Cumulative meta-analysis of clinical trials builds evidence for exemplary medical care. J Clin Epidemiol 1995, 48(1):45-57 
  • Bagos PG, Nikolopoulos GK. Generalized least squares for assessing trends in cumulative meta-analysis with applications in genetic epidemiology. 2009, Journal of Clinical Epidemiology, 62 (10): 1037-1044 [PDF]
  • Ioannidis JPA, Lau J: Evolution of treatment effects over time: Empirical insight from recursive cumulative metaanalyses. Proc Natl Acad Sci U S A 2001, 98:831-836. [PDF]

  • Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics 1994, 50:1088-1101.
  • Duval S, Tweedie R. A nonparametric "trim and fill" method of accounting for publication bias in meta-analysis. JASA 2000, 95(449):89-98. [PPT]
  • Thornton A, Lee P. Publication bias in meta-analysis: its causes and consequences. J Clin Epidemiol 2000, 53(2):207-216.
  • Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. Bmj 1997, 315(7109):629-634. [PDF]
  • Arends LR, Hamza TH, van Houwelingen JC, Heijenbrok-Kal MH, Hunink MG, Stijnen T. Bivariate random effects meta-analysis of ROC curves. Med Decis Making 2008, 28(5):621-638.
  • Higgins JPT, Thompson SG, Deeks JJ, Altman DG: Measuring inconsistency in meta-analyses. BMJ 2003, 327:557-560.  [PDF]

  • Higgins JP, Thompson SG, Spiegelhalter DJ. A re-evaluation of random-effects meta-analysis. J R Stat Soc Ser A Stat Soc. 2009 Jan;172(1):137-159.  [PDF]
  • Jackson D, Riley R, White IR.Multivariate meta-analysis: Potential and promise. Stat Med. 2011 Jan 26. doi: 10.1002/sim.4172. [Epub ahead of print]

For meta-analysis of genetic-association studies, see the respective page on Genetic Epidemiology