Abstract
Meta-analysis is a common feature of quantitative synthesis for systematic reviews, one of the four archetypes in this book.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
By some the replication continuum is attributed to the work of Lipsey and Wilson (1993). However, there is no mention of it. Also, the statement ‘the closer to pure replications your collection of studies, the easier it is to argue comparability’ does not appear in the text of Lipsey and Wilson nor can it be interpreted as a paraphrased statement. This means caution is required when looking for the origins of the replication continuum.
- 2.
Hendrick (1990) refers to a working paper written by him in 1974 about the dichotomy ‘strict replication’ and ‘conceptual replication.’
- 3.
- 4.
The other two of the three preceding systematic reviews with meta-analysis were dated fifteen years before this systematic review using the odds ratio for conducting the meta-analysis.
- 5.
The authors do not use the term ‘grey literature’, which is introduced here for consistency of terminology in the book.
- 6.
See Section 3.3 for more detail on ontology in the context of research paradigms.
- 7.
See Dickersin (1990, pp. 1385–1386) for some historical notes with regard to publication bias.
References
Aguinis H, Pierce CA, Bosco FA, Dalton DR, Dalton CM (2011) Debunking myths and urban legends about meta-analysis. Organ Res Methods 14(2):306–331. https://doi.org/10.1177/1094428110375720
Allen M, Preiss R (1993) Replication and meta-analysis: a necessary connection. J Soc Behav Pers 8(6):9–20
Animasaun IL, Ibraheem RO, Mahanthesh B, Babatunde HA (2019) A meta-analysis on the effects of haphazard motion of tiny/nano-sized particles on the dynamics and other physical properties of some fluids. Chin J Phys 60:676–687. https://doi.org/10.1016/j.cjph.2019.06.007
Anzures-Cabrera J, Higgins JPT (2010) Graphical displays for meta-analysis: an overview with suggestions for practice. Res Synth Methods 1(1):66–80. https://doi.org/10.1002/jrsm.6
Bakbergenuly I, Hoaglin DC, Kulinskaya E (2019) Pitfalls of using the risk ratio in meta-analysis. Res Synth Methods 10(3):398–419. https://doi.org/10.1002/jrsm.1347
Bakbergenuly I, Kulinskaya E (2017) Beta-binomial model for meta-analysis of odds ratios. Stat Med 36(11):1715–1734. https://doi.org/10.1002/sim.7233
Baker WL, Michael White C,Cappelleri JC, Kluger J, Coleman CI, From the Health Outcomes P, Group EC (2009) Understanding heterogeneity in meta‐analysis: the role of meta‐regression. Int J Clin Pract 63(10):1426–1434. https://doi.org/10.1111/j.1742-1241.2009.02168.x
Bax L, Ikeda N, Fukui N, Yaju Y, Tsuruta H, Moons KGM (2008) More than numbers: the power of graphs in meta-analysis. Am J Epidemiol 169(2):249–255. https://doi.org/10.1093/aje/kwn340
Bax L, Yu L-M, Ikeda N, Moons KGM (2007) A systematic comparison of software dedicated to meta-analysis of causal studies. BMC Med Res Methodol 7(1):40. https://doi.org/10.1186/1471-2288-7-40
Bender R, Bunce C, Clarke M, Gates S, Lange S, Pace NL, Thorlund K (2008) Attention should be given to multiplicity issues in systematic reviews. J Clin Epidemiol 61(9):857–865. https://doi.org/10.1016/j.jclinepi.2008.03.004
Bennett DA, Latham NK, Stretton C, Anderson CS (2004) Capture-recapture is a potentially useful method for assessing publication bias. J Clin Epidemiol 57(4):349–357. https://doi.org/10.1016/j.jclinepi.2003.09.015
Biggerstaff BJ, Tweedie RL (1997) Incorporating variability in estimates of heterogeneity in the random effects model in meta-analysis. Stat Med 16(7):753–768. https://doi.org/10.1002/(SICI)1097-0258(19970415)16:7<753::AID-SIM494>3.0.CO;2-G
Blyth CR (1972) On Simpson’s paradox and the sure-thing principle. J Am Stat Assoc 67(338):364–366. https://doi.org/10.1080/01621459.1972.10482387
Borenstein M, Hedges LV, Higgins JPT, Rothstein HR (2010) A basic introduction to fixed-effect and random-effects models for meta-analysis. Res Synth Methods 1(2):97–111. https://doi.org/10.1002/jrsm.12
Bravata DM, Olkin I (2001) Simple pooling versus combining in meta-analysis. Eval Health Prof 24(2):218–230. https://doi.org/10.1177/01632780122034885
Brown SA, Upchurch SL, Acton GJ (2003) A framework for developing a coding scheme for meta-analysis. West J Nurs Res 25(2):205–222. https://doi.org/10.1177/0193945902250038
Cheung MW-L, Ho RCM, Lim Y, Mak A (2012) Conducting a meta-analysis: basics and good practices. Int J Rheum Dis 15(2):129–135. https://doi.org/10.1111/j.1756-185X.2012.01712.x
Chiolero A, Santschi V, Burnand B, Platt RW, Paradis G (2012) Meta-analyses: with confidence or prediction intervals? Eur J Epidemiol 27(10):823–825. https://doi.org/10.1007/s10654-012-9738-y
Chootrakool H, Shi JQ, Yue R (2011) Meta-analysis and sensitivity analysis for multi-arm trials with selection bias. Stat Med 30(11):1183–1198. https://doi.org/10.1002/sim.4143
Chow SL (1987) Meta-analysis of pragmatic and theoretical research: a critique. J Psychol 121(3):259–271. https://doi.org/10.1080/00223980.1987.9712666
Copas JB (2013) A likelihood-based sensitivity analysis for publication bias in meta-analysis. J Roy Stat Soc Ser C (Appl Stat) 62(1):47–66. https://doi.org/10.1111/j.1467-9876.2012.01049.x
Copas J, Shi JQ (2000) Meta-analysis, funnel plots and sensitivity analysis. Biostatistics 1(3):247–262. https://doi.org/10.1093/biostatistics/1.3.247
Copas JB, Shi JQ (2001) A sensitivity analysis for publication bias in systematic reviews. Stat Methods Med Res 10(4):251–265. https://doi.org/10.1177/096228020101000402
Cortoni F, Babchishin KM, Rat C (2017) The proportion of sexual offenders who are female is higher than thought: a meta-analysis. Crim Justice Behav 44(2):145–162. https://doi.org/10.1177/0093854816658923
Dalton JE, Bolen SD, Mascha EJ (2016) Publication bias: the elephant in the review. Anesth Analg 123(4):812–813. https://doi.org/10.1213/ane.0000000000001596
De Wolff MS, van Ijzendoorn MH (1997) Sensitivity and attachment: a meta-analysis on parental antecedents of infant attachment. Child Dev 68(4):571–591. https://doi.org/10.1111/j.1467-8624.1997.tb04218.x
Deeks JJ, Higgins JPT, Altman DG (2021) Analysing data and undertaking meta-analyses. In: Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (eds) Cochrane handbook for systematic reviews of interventions (Version 6.2 ed): cochrane. https://training.cochrane.org/handbook/current/chapter-10
DerSimonian R, Laird N (1986) Meta-analysis in clinical trials. Control Clin Trials 7(3):177–188. https://doi.org/10.1016/0197-2456(86)90046-2
Dickersin K (1990) The existence of publication bias and risk factors for its occurrence. JAMA 263(10):1385–1389. https://doi.org/10.1001/jama.1990.03440100097014
Doucouliagos H, Ulubaşoğlu MA (2008) Democracy and economic growth: a meta-analysis. Am J Polit Sci 52(1):61–83. https://doi.org/10.1111/j.1540-5907.2007.00299.x
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):455–463. https://doi.org/10.1111/j.0006-341X.2000.00455.x
Egger M, Smith GD, Phillips AN (1997) Meta-analysis: principles and procedures. BMJ 315(7121):1533–1537. https://doi.org/10.1136/bmj.315.7121.1533
Egger M, Smith GD, Schneider M, Minder C (1997) Bias in meta-analysis detected by a simple, graphical test. BMJ 315(7109):629–634. https://doi.org/10.1136/bmj.315.7109.629
Elvik R (2005) Can we trust the results of meta-analyses?: a systematic approach to sensitivity analysis in meta-analyses. Transp Res Rec 1908(1):221–229. https://doi.org/10.1177/0361198105190800127
Ewing R, Cervero R (2010) Travel and the built environment. J Am Plan Assoc 76(3):265–294. https://doi.org/10.1080/01944361003766766
Franco A, Malhotra N, Simonovits G (2014) Publication bias in the social sciences: unlocking the file drawer. Science 345(6203):1502–1505. https://doi.org/10.1126/science.1255484
Galbraith RF (1988) A note on graphical presentation of estimated odds ratios from several clinical trials. Stat Med 7(8):889–894. https://doi.org/10.1002/sim.4780070807
Glass GV (1976) Primary, secondary, and meta-analysis of research. Educ Res 5(10):3–8. https://doi.org/10.3102/0013189X005010003
Göritz AS (2006) Incentives in web studies: methodological issues and a review. Int J Internet Sci 1(1):58–70
Gøtzsche PC, Hróbjartsson A, Marić K, Tendal B (2007) Data extraction errors in meta-analyses that use standardized mean differences. JAMA 298(4):430–437. https://doi.org/10.1001/jama.298.4.430
Govindan K, Rajeev A, Padhi SS, Pati RK (2020) Supply chain sustainability and performance of firms: a meta-analysis of the literature. Transp Res Part E Logist Transp Rev 137:101923. https://doi.org/10.1016/j.tre.2020.101923
Guzzo RA, Jackson SE, Katzell RA (1987) Meta-analysis analysis. Res Organ Behav 9:407–442
Hartung J, Knapp G (2001) A refined method for the meta-analysis of controlled clinical trials with binary outcome. Stat Med 20(24):3875–3889. https://doi.org/10.1002/sim.1009
Hendrick C (1990) Replications, strict replications, and conceptual replications: are they important? J Soc Behav Personal 5(4):41–49
Higgins JPT, Thompson SG (2002) Quantifying heterogeneity in a meta-analysis. Stat Med 21(11):1539–1558. https://doi.org/10.1002/sim.1186
Higgins JPT, Thompson SG, Deeks JJ, Altman DG (2003) Measuring inconsistency in meta-analyses. BMJ 327(7414):557–560. https://doi.org/10.1136/bmj.327.7414.557
Hoobler JM, Masterson CR, Nkomo SM, Michel EJ (2018) The business case for women leaders: meta-analysis, research critique, and path forward. J Manag 44(6):2473–2499. https://doi.org/10.1177/0149206316628643
Hook EB, Regal RR (1995) Capture-recapture methods in epidemiology: methods and limitations. Epidemiol Rev 17(2):243–264. https://doi.org/10.1093/oxfordjournals.epirev.a036192
Howard GS, Maxwell SE (1980) Correlation between student satisfaction and grades: a case of mistaken causation? J Educ Psychol 72(6):810–820. https://doi.org/10.1037/0022-0663.72.6.810
IntHout J, Ioannidis JPA, Borm GF (2014) The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method. BMC Med Res Methodol 14(1):25. https://doi.org/10.1186/1471-2288-14-25
Itani O, Jike M, Watanabe N, Kaneita Y (2017) Short sleep duration and health outcomes: a systematic review, meta-analysis, and meta-regression. Sleep Med 32:246–256. https://doi.org/10.1016/j.sleep.2016.08.006
Kaufmann E, Reips U-D, Maag Merki K (2016) Avoiding methodological biases in meta-analysis. Zeitschrift Für Psychologie 224(3):157–167. https://doi.org/10.1027/2151-2604/a000251
Kim KH (2005) Can only intelligent people be creative? A meta-analysis. J Second Gift Educ 16(2–3):57–66. https://doi.org/10.4219/jsge-2005-473
Kontopantelis E, Reeves D (2012) Performance of statistical methods for meta-analysis when true study effects are non-normally distributed: a simulation study. Stat Methods Med Res 21(4):409–426. https://doi.org/10.1177/0962280210392008
Kontopantelis E, Reeves D (2012) Performance of statistical methods for meta-analysis when true study effects are non-normally distributed: a comparison between DerSimonian–Laird and restricted maximum likelihood. Stat Methods Med Res 21(6):657–659. https://doi.org/10.1177/0962280211413451
L’Abbé KA, Detsky AS, O’Rourke K (1987) Meta-analysis in clinical research. Ann Intern Med 107(2):224–233. https://doi.org/10.7326/0003-4819-107-2-224
Lajeunesse MJ (2016) Facilitating systematic reviews, data extraction and meta-analysis with the metagear package for R. Methods Ecol Evol 7(3):323–330. https://doi.org/10.1111/2041-210X.12472
Lakens D (2013) Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Front Psychol 4(863). https://doi.org/10.3389/fpsyg.2013.00863
Lipsey MW, Wilson DB (1993) The efficacy of psychological, educational, and behavioral treatment: confirmation from meta-analysis. Am Psychol 48(12):1181–1209. https://doi.org/10.1037/0003-066X.48.12.1181
Lloyd S, Schmidt U, Khondoker M, Tchanturia K (2015) Can psychological interventions reduce perfectionism? A systematic review and meta-analysis. Behav Cogn Psychother 43(6):705–731. https://doi.org/10.1017/S1352465814000162
Lopes JSS, Machado AF, Cavina AP, Kirsch Michelletti J, Castilho de Almeida A, Pastre CM (2019) Specific interventions for prevention of muscle injury in lower limbs: systematic review and meta-analysis. Fisioterapia Movimento 32:e003224. https://doi.org/10.1590/1980-5918.032.AO24
López-López JA, Page MJ, Lipsey MW, Higgins JPT (2018) Dealing with effect size multiplicity in systematic reviews and meta-analyses. Res Synth Methods 9(3):336–351. https://doi.org/10.1002/jrsm.1310
Macaskill P, Walter SD, Irwig L (2001) A comparison of methods to detect publication bias in meta-analysis. Stat Med 20(4):641–654. https://doi.org/10.1002/sim.698
Mathes T, Kuss O (2018) A comparison of methods for meta-analysis of a small number of studies with binary outcomes. Res Synth Methods 9(3):366–381. https://doi.org/10.1002/jrsm.1296
Mantel N, Haenszel W (1959) Statistical aspects of the analysis of data from retrospective studies of disease. JNCI J Nat Cancer Inst 22(4):719–748. https://doi.org/10.1093/jnci/22.4.719
Mavros MN, Alexiou VG, Vardakas KZ, Falagas ME (2013) Understanding of statistical terms routinely used in meta-analyses: an international survey among researchers. PLoS One 8(1):e47229. https://doi.org/10.1371/journal.pone.0047229
McDaniel MA, Rothstein HR, Whetzel DL (2006) Publication bias: a case study of four test vendors. Pers Psychol 59(4):927–953. https://doi.org/10.1111/j.1744-6570.2006.00059.x
McKenzie JE, Beller EM, Forbes AB (2016) Introduction to systematic reviews and meta-analysis. Respirology 21(4):626–637. https://doi.org/10.1111/resp.12783
McShane BB, Böckenholt U (2017) Single-paper meta-analysis: benefits for study summary, theory testing, and replicability. J Consum Res 43(6):1048–1063. https://doi.org/10.1093/jcr/ucw085
Munn Z, Tufanaru C, Aromataris E (2014) JBI’s systematic reviews: data extraction and synthesis. AJN Am J Nurs 114(7):49–54. https://doi.org/10.1097/01.Naj.0000451683.66447.89
Nakagawa S, Noble DWA, Senior AM, Lagisz M (2017) Meta-evaluation of meta-analysis: ten appraisal questions for biologists. BMC Biol 15(1):18. https://doi.org/10.1186/s12915-017-0357-7
Neyeloff JL, Fuchs SC, Moreira LB (2012) Meta-analyses and forest plots using a microsoft excel spreadsheet: step-by-step guide focusing on descriptive data analysis. BMC Res Notes 5(1):52. https://doi.org/10.1186/1756-0500-5-52
O’Keefe DJ, Hale SL (2001) An odds-ratio-based meta-analysis of research on the door-in-the-face influence strategy. Commun Rep 14(1):31–38. https://doi.org/10.1080/08934210109367734
Pastor DA, Lazowski RA (2018) On the multilevel nature of meta-analysis: a tutorial, comparison of software programs, and discussion of analytic choices. Multivar Behav Res 53(1):74–89. https://doi.org/10.1080/00273171.2017.1365684
Pearson K, Lee A, Bramley-Moore L (1899) VI. Mathematical contributions to the theory of evolution–VI. Genetic (Reproductive) selection: inheritance of fertility in man, and of fecundity in thoroughbred racehorses. Philos Trans R Soc Lond 192:257–330. https://doi.org/10.1098/rsta.1899.0006
Pedder H, Sarri G, Keeney E, Nunes V, Dias S (2016) Data extraction for complex meta-analysis (DECiMAL) guide. Syst Rev 5(1):212. https://doi.org/10.1186/s13643-016-0368-4
Philibert A, Loyce C, Makowski D (2012) Assessment of the quality of meta-analysis in agronomy. Agr Ecosyst Environ 148:72–82. https://doi.org/10.1016/j.agee.2011.12.003
Pigott TD, Polanin JR (2020) Methodological guidance paper: high-quality meta-analysis in a systematic review. Rev Educ Res 90(1):24–46. https://doi.org/10.3102/0034654319877153
Polák P (2017) The productivity paradox: a meta-analysis. Inf Econ Policy 38:38–54. https://doi.org/10.1016/j.infoecopol.2016.11.003
Poorolajal J, Haghdoost AA, Mahmoodi M, Majdzadeh R, Nasseri-Moghaddam S, Fotouhi A (2010) Capture-recapture method for assessing publication bias. J Res Med Sci 15(2):107–115
Rice K, Higgins JPT, Lumley T (2018) A re-evaluation of fixed effect(s) meta-analysis. J R Stat Soc A Stat Soc 181(1):205–227. https://doi.org/10.1111/rssa.12275
Rosenthal R (1979) The “File Drawer Problem” and tolerance for null results. Psychol Bull 86(3):638–641. https://doi.org/10.1037/0033-2909.86.3.638
Russo MW (2007) How to review a meta-analysis. Gastroenterol Hepatol 3(8):637–642
Schmid EJ, Koch GG, LaVange LM (1991) An overview of statistical issues and methods of meta-analysis. J Biopharm Stat 1(1):103–120. https://doi.org/10.1080/10543409108835008
Schmidt FL (2017) Statistical and measurement pitfalls in the use of meta-regression in meta-analysis. Career Dev Int 22(5):469–476. https://doi.org/10.1108/CDI-08-2017-0136
Schmidt FL, Oh I-S, Hayes TL (2009) Fixed-versus random-effects models in meta-analysis: model properties and an empirical comparison of differences in results. Br J Math Stat Psychol 62(1):97–128. https://doi.org/10.1348/000711007X255327
Sera F, Armstrong B, Blangiardo M, Gasparrini A (2019) An extended mixed-effects framework for meta-analysis. Stat Med 38(29):5429–5444. https://doi.org/10.1002/sim.8362
Shah SA, Sander S, White CM, Rinaldi M, Coleman CI (2007) Evaluation of echinacea for the prevention and treatment of the common cold: a meta-analysis. Lancet Infect Dis 7(7):473–480. https://doi.org/10.1016/S1473-3099(07)70160-3
Sidik K, Jonkman JN (2006) Robust variance estimation for random effects meta-analysis. Comput Stat Data Anal 50(12):3681–3701. https://doi.org/10.1016/j.csda.2005.07.019
Song F, Sheldon TA, Sutton AJ, Abrams KR, Jones DR (2001) Methods for exploring heterogeneity in meta-analysis. Eval Health Prof 24(2):126–151. https://doi.org/10.1177/016327870102400203
Simpson EH (1951) The interpretation of interaction in contingency tables. J Roy Stat Soc Ser B (Methodol) 13(2):238–241. https://doi.org/10.1111/j.2517-6161.1951.tb00088.x
Stanley TD (2001) Wheat from chaff: meta-analysis as quantitative literature review. J Econ Perspect 15(3):131–150. https://doi.org/10.1257/jep.15.3.131
Stanley TD, Doucouliagos H (2015) Neither fixed nor random: weighted least squares meta-analysis. Stat Med 34(13):2116–2127. https://doi.org/10.1002/sim.6481
Stanley TD, Doucouliagos H, Giles M, Heckemeyer JH, Johnston RJ, Laroche P, Nelson JP, Paldam M, Poot J, Pugh G, Rosenberger RS, Rost K (2013) Meta-analysis of economics research reporting guidelines. J Econ Surv 27(2):390–394. https://doi.org/10.1111/joes.12008
Stanley TD, Jarrell SB (2005) Meta-regression analysis: a quantitative method of literature surveys. J Econ Surv 19(3):299–308. https://doi.org/10.1111/j.0950-0804.2005.00249.x
Sutton AJ, Abrams KR (2001) Bayesian methods in meta-analysis and evidence synthesis. Stat Methods Med Res 10(4):277–303. https://doi.org/10.1177/096228020101000404
Sutton AJ, Higgins JPT (2008) Recent developments in meta-analysis. Stat Med 27(5):625–650. https://doi.org/10.1002/sim.2934
Suurmond R, van Rhee H, Hak T (2017) Introduction, comparison, and validation of Meta-Essentials: a free and simple tool for meta-analysis. Res Synth Methods 8(4):537–553. https://doi.org/10.1002/jrsm.1260
Takeshima N, Sozu T, Tajika A, Ogawa Y, Hayasaka Y, Furukawa TA (2014) Which is more generalizable, powerful and interpretable in meta-analyses, mean difference or standardized mean difference? BMC Med Res Methodol 14(1):30. https://doi.org/10.1186/1471-2288-14-30
Tang S-H, Hall VC (1995) The overjustification effect: a meta-analysis. Appl Cogn Psychol 9(5):365–404. https://doi.org/10.1002/acp.2350090502
Tendal B, Nüesch E, Higgins JPT, Jüni P, Gøtzsche PC (2011) Multiplicity of data in trial reports and the reliability of meta-analyses: empirical study. BMJ 343:d4829. https://doi.org/10.1136/bmj.d4829
Terrin N, Schmid CH, Lau J, Olkin I (2003) Adjusting for publication bias in the presence of heterogeneity. Stat Med 22(13):2113–2126. https://doi.org/10.1002/sim.1461
Thompson SG, Higgins JPT (2002) How should meta-regression analyses be undertaken and interpreted? Stat Med 21(11):1559–1573. https://doi.org/10.1002/sim.1187
Tipton E, Pustejovsky JE, Ahmadi H (2019) A history of meta-regression: technical, conceptual, and practical developments between 1974 and 2018. Res Synth Methods 10(2):161–179. https://doi.org/10.1002/jrsm.1338
Uttl B, White CA, Gonzalez DW (2017) Meta-analysis of faculty’s teaching effectiveness: student evaluation of teaching ratings and student learning are not related. Stud Educ Eval 54:22–42. https://doi.org/10.1016/j.stueduc.2016.08.007
van Houwelingen HC, Arends LR, Stijnen T (2002) Advanced methods in meta-analysis: multivariate approach and meta-regression. Stat Med 21(4):589–624. https://doi.org/10.1002/sim.1040
Verhaeghen P (2003) Aging and vocabulary score: a meta-analysis. Psychol Aging 18(2):332–339. https://doi.org/10.1037/0882-7974.18.2.332
Veroniki AA, Jackson D, Bender R, Kuss O, Langan D, Higgins JPT, Knapp G, Salanti G (2019) Methods to calculate uncertainty in the estimated overall effect size from a random-effects meta-analysis. Res Synth Methods 10(1):23–43. https://doi.org/10.1002/jrsm.1319
Viechtbauer W (2007) Confidence intervals for the amount of heterogeneity in meta-analysis. Stat Med 26(1):37–52. https://doi.org/10.1002/sim.2514
Walker HM (1940) Degrees of freedom. J Educ Psychol 31(4):253–269. https://doi.org/10.1037/h0054588
Wanous JP, Sullivan SE, Malinak J (1989) The role of judgment calls in meta-analysis. J Appl Psychol 74(2):259–264. https://doi.org/10.1037/0021-9010.74.2.259
Woodward ND, Purdon SE, Meltzer HY, Zald DH (2005) A meta-analysis of neuropsychological change to clozapine, olanzapine, quetiapine, and risperidone in schizophrenia. Int J Neuropsychopharmacol 8(3):457–472. https://doi.org/10.1017/s146114570500516x
Yule GU (1903) Notes on the Theory of Association of Attributes in Statistics. Biometrika 2(2):121–134. https://doi.org/10.2307/2331677
Yusuf S, Peto R, Lewis J, Collins R, Sleight P (1985) Beta blockade during and after myocardial infarction: an overview of the randomized trials. Prog Cardiovasc Dis 27(5):335–371. https://doi.org/10.1016/S0033-0620(85)80003-7
Zeng Y, Luo T, Xie H, Huang M, Cheng ASK (2014) Health benefits of qigong or tai chi for cancer patients: a systematic review and meta-analyses. Complement Ther Med 22(1):173–186. https://doi.org/10.1016/j.ctim.2013.11.010
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2022 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Dekkers, R., Carey, L., Langhorne, P. (2022). Principles of Meta-Analysis. In: Making Literature Reviews Work: A Multidisciplinary Guide to Systematic Approaches. Springer, Cham. https://doi.org/10.1007/978-3-030-90025-0_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-90025-0_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-90024-3
Online ISBN: 978-3-030-90025-0
eBook Packages: EducationEducation (R0)