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Journal articles on the topic 'Statistical meta-analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Kang, Hyun. "Statistical Considerations in Meta-Analysis." Hanyang Medical Reviews 35, no. 1 (2015): 23. http://dx.doi.org/10.7599/hmr.2015.35.1.23.

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2

Freeman, P. R., L. V. Hedges, and I. Olkin. "Statistical Methods for Meta-Analysis." Biometrics 42, no. 2 (1986): 454. http://dx.doi.org/10.2307/2531069.

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3

Berk, Richard. "Statistical inference and meta-analysis." Journal of Experimental Criminology 3, no. 3 (2007): 247–70. http://dx.doi.org/10.1007/s11292-007-9036-y.

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4

Wasserman, Stanley, Larry V. Hedges, and Ingram Olkin. "Statistical Methods for Meta-Analysis." Journal of Educational Statistics 13, no. 1 (1988): 75. http://dx.doi.org/10.2307/1164953.

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5

Rosenbaum, Paul R., Larry Hedges, and Ingram Olkin. "Statistical Methods for Meta-Analysis." Journal of the American Statistical Association 82, no. 397 (1987): 350. http://dx.doi.org/10.2307/2289186.

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6

Barza, Michael, Thomas A. Trikalinos, and Joseph Lau. "Statistical Considerations in Meta-analysis." Infectious Disease Clinics of North America 23, no. 2 (2009): 195–210. http://dx.doi.org/10.1016/j.idc.2009.01.003.

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7

Cohn, Lawrence D., and Betsy J. Becker. "How meta-analysis increases statistical power." Psychological Methods 8, no. 3 (2003): 243–53. http://dx.doi.org/10.1037/1082-989x.8.3.243.

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8

Osenberg, Craig W., and Colette M. St. Mary. "Meta-analysis: Synthesis or statistical subjugation?" Integrative Biology: Issues, News, and Reviews 1, no. 1 (1998): 37–41. http://dx.doi.org/10.1002/(sici)1520-6602(1998)1:1<37::aid-inbi5>3.0.co;2-0.

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9

Hedges, Larry V. "Meta-Analysis." Journal of Educational Statistics 17, no. 4 (1992): 279–96. http://dx.doi.org/10.3102/10769986017004279.

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The use of statistical methods to combine the results of independent empirical research studies (meta-analysis) has a long history. Meta-analytic work can be divided into two traditions: tests of the statistical significance of combined results and methods for combining estimates across studies. The principal classes of combined significance tests are reviewed, and the limitations of these tests are discussed. Fixed effects approaches treat the effect magnitude parameters to be estimated as a consequence of a model involving fixed but unknown constants. Random effects approaches treat effect m

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10

Sohani, Zahra. "Meta-analysis: Statistical Trickery or Sound Science?" Journal of Postgraduate Medicine, Education and Research 46, no. 1 (2012): 12–14. http://dx.doi.org/10.5005/jp-journals-10028-1004.

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ABSTRACT The goal of a systematic review is to present a balanced summary of existing research. In order to accomplish this, systematic reviews include a thorough search of relevant articles, including published and unpublished, using explicitly defined and reproducible criteria. The main rationale for conducting a meta-analysis comes from the fact that combining individual studies provide an increased sample size, which consequently improves the statistical power to detect treatment effect. If all steps outlined are followed properly and authors remain transparent regarding the design and con

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11

Peterman, R. "Statistical power of methods of meta-analysis." Trends in Ecology & Evolution 10, no. 11 (1995): 460. http://dx.doi.org/10.1016/s0169-5347(00)89180-6.

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12

Olkin, Ingram. "Statistical and theoretical considerations in meta-analysis." Journal of Clinical Epidemiology 48, no. 1 (1995): 133–46. http://dx.doi.org/10.1016/0895-4356(94)00136-e.

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13

Davies, Annabel L., and Tobias Galla. "Network meta-analysis: a statistical physics perspective." Journal of Statistical Mechanics: Theory and Experiment 2022, no. 11 (2022): 11R001. http://dx.doi.org/10.1088/1742-5468/ac9463.

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Abstract Network meta-analysis (NMA) is a technique used in medical statistics to combine evidence from multiple medical trials. NMA defines an inference and information processing problem on a network of treatment options and trials connecting the treatments. We believe that statistical physics can offer useful ideas and tools for this area, including from the theory of complex networks, stochastic modelling and simulation techniques. The lack of a unique source that would allow physicists to learn about NMA effectively is a barrier to this. In this article we aim to present the ‘NMA problem’

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14

Sánchez-Meca, Julio, and Fulgencio Marín-Martínez. "Meta-analysis in psychological research." International Journal of Psychological Research 3, no. 1 (2010): 150–62. http://dx.doi.org/10.21500/20112084.860.

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Meta-analysis is a research methodology that aims to quantitatively integrate the results of a set of empirical studies about a given topic. With this purpose, effect-size indices are obtained from the individual studies and the characteristics of the studies are coded in order to examine their relationships with the effect sizes. Statistical analysis in meta-analysis requires the weighting of each effect estimate as a function of its precision, by assuming a fixed- or a random-effects model. This paper outlines the steps required for carrying out the statistical analyses in a meta-analysis, t

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15

Banzhaf, H. Spencer. "The Value of Statistical Life: A Meta-Analysis of Meta-Analyses." Journal of Benefit-Cost Analysis 13, no. 2 (2022): 182–97. http://dx.doi.org/10.1017/bca.2022.9.

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AbstractThe value of statistical life (VSL) is arguably the most important number in benefit–cost analyses of environmental, health, and transportation policies. However, agencies have used a wide range of VSL values. One reason may be the embarrassment of riches when it comes to VSL studies. While meta-analysis is a standard way to synthesize information across studies, we now have multiple competing meta-analyses and reviews. Thus, to analysts, picking one such meta-analysis may feel as hard as picking a single “best study.” This article responds by taking the meta-analysis another step, est

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16

Madden, L. V., H. P. Piepho, and P. A. Paul. "Statistical Models and Methods for Network Meta-Analysis." Phytopathology® 106, no. 8 (2016): 792–806. http://dx.doi.org/10.1094/phyto-12-15-0342-rvw.

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Meta-analysis, the methodology for analyzing the results from multiple independent studies, has grown tremendously in popularity over the last four decades. Although most meta-analyses involve a single effect size (summary result, such as a treatment difference) from each study, there are often multiple treatments of interest across the network of studies in the analysis. Multi-treatment (or network) meta-analysis can be used for simultaneously analyzing the results from all the treatments. However, the methodology is considerably more complicated than for the analysis of a single effect size,

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17

Tang, Liansheng Larry, Michael Caudy, and Faye Taxman. "A Statistical Method for Synthesizing Meta-Analyses." Computational and Mathematical Methods in Medicine 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/732989.

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Multiple meta-analyses may use similar search criteria and focus on the same topic of interest, but they may yield different or sometimes discordant results. The lack of statistical methods for synthesizing these findings makes it challenging to properly interpret the results from multiple meta-analyses, especially when their results are conflicting. In this paper, we first introduce a method to synthesize the meta-analytic results when multiple meta-analyses use the same type of summary effect estimates. When meta-analyses use different types of effect sizes, the meta-analysis results cannot

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18

Griffin, Jason W. "Calculating statistical power for meta-analysis using metapower." Quantitative Methods for Psychology 17, no. 1 (2021): 24–39. http://dx.doi.org/10.20982/tqmp.17.1.p024.

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19

Kelley, George A. "Statistical models for meta-analysis: A brief tutorial." World Journal of Methodology 2, no. 4 (2012): 27. http://dx.doi.org/10.5662/wjm.v2.i4.27.

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20

Mullen, Brian. "BASIC meta-analysis: Description of a statistical package." Behavior Research Methods, Instruments, & Computers 18, no. 2 (1986): 165–67. http://dx.doi.org/10.3758/bf03201018.

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21

Majumder, Agamoni, and S. Madheswaran. "Meta-analysis of Value of Statistical Life Estimates." IIM Kozhikode Society & Management Review 6, no. 1 (2017): 110–20. http://dx.doi.org/10.1177/2277975216678546.

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Value of Statistical Life (VSL) is one of the most debatable areas in economics. However, VSL is frequently used as a policy instrument for evaluating various safety, health and environmental regulations. Policymakers have to undertake the difficult task of assigning monetary value to the reduction of various health and mortality risks while analyzing safety policies. Compensating wage differential (CWD) for job risks acts as a reference point for valuing mortality risks while VSL serves as a basis to analyze these benefits of risk reduction policies. However, it has been observed in the recen

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22

Fleiss, JL. "Review papers : The statistical basis of meta-analysis." Statistical Methods in Medical Research 2, no. 2 (1993): 121–45. http://dx.doi.org/10.1177/096228029300200202.

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23

Hedges, Larry V., and Therese D. Pigott. "The power of statistical tests in meta-analysis." Psychological Methods 6, no. 3 (2001): 203–17. http://dx.doi.org/10.1037/1082-989x.6.3.203.

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24

Samartzis, Dino, and Rafael Perera. "Meta-analysis: statistical methods for binary data pooling." Spine Journal 9, no. 5 (2009): 424–25. http://dx.doi.org/10.1016/j.spinee.2009.01.011.

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25

Feinstein, Alvan R. "Meta-analysis: Statistical alchemy for the 21st century." Journal of Clinical Epidemiology 48, no. 1 (1995): 71–79. http://dx.doi.org/10.1016/0895-4356(94)00110-c.

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26

Fleiss, Joseph L. "“Statistical and theoretical considerations in meta-analysis”: Discussion." Journal of Clinical Epidemiology 48, no. 1 (1995): 147. http://dx.doi.org/10.1016/0895-4356(94)00113-5.

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27

Eger, Robert J., and J. Haavard Maridal. "A statistical meta-analysis of the wellbeing literature." International Journal of Wellbeing 5, no. 2 (2015): 45–74. http://dx.doi.org/10.5502/ijw.v5i2.4.

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28

Spineli, Loukia M., and Nikolaos Pandis. "Statistical heterogeneity: Notion and estimation in meta-analysis." American Journal of Orthodontics and Dentofacial Orthopedics 157, no. 6 (2020): 856–59. http://dx.doi.org/10.1016/j.ajodo.2020.03.009.

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29

Brockwell, Sarah E., and Ian R. Gordon. "A comparison of statistical methods for meta-analysis." Statistics in Medicine 20, no. 6 (2001): 825–40. http://dx.doi.org/10.1002/sim.650.

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30

Arnold, Matthias M., Andreas W. Rathgeber, and Stefan Stöckl. "Determinants of corporate hedging: A (statistical) meta-analysis." Quarterly Review of Economics and Finance 54, no. 4 (2014): 443–58. http://dx.doi.org/10.1016/j.qref.2014.05.002.

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31

Tu, Yu-Kang, and Clovis Mariano Faggion. "A Primer on Network Meta-Analysis for Dental Research." ISRN Dentistry 2012 (June 21, 2012): 1–10. http://dx.doi.org/10.5402/2012/276520.

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In the last decade, a new statistical methodology, namely, network meta-analysis, has been developed to address limitations in traditional pairwise meta-analysis. Network meta-analysis incorporates all available evidence into a general statistical framework for comparisons of all available treatments. A further development in the network meta-analysis is to use a Bayesian statistical approach, which provides a more flexible modelling framework to take into account heterogeneity in the evidence and complexity in the data structure. The aim of this paper is therefore to provide a nontechnical in

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32

Dexter, Franklin. "Statistical analysis methods for meta-analysis of times to emergence." European Journal of Anaesthesiology 32, no. 7 (2015): 506. http://dx.doi.org/10.1097/eja.0000000000000254.

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33

Schulze, Ralf. "Current Methods for Meta-Analysis." Zeitschrift für Psychologie / Journal of Psychology 215, no. 2 (2007): 90–103. http://dx.doi.org/10.1027/0044-3409.215.2.90.

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Abstract. The bulk of conceptual and statistical developments as well as applications of meta-analysis have been published in the last 30 years. The methods for meta-analysis continue to be refined and new methods are applied to new types of research questions and data. Such current approaches, issues, and developments prevalent in the behavioral sciences are presented, reviewed, and discussed in this paper. The areas that are covered include: the fixed effects and random effects model of meta-analysis, new findings concerning effect sizes and their statistical properties, the comparison of di

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34

Palpal-latoc, Leinard, and Carmelo Braganza. "Meta-analysis of Randomized Controlled Trials." Philippine Journal of Orthopaedics 40, no. 1 (2025): 51–59. https://doi.org/10.69472/poai.2025.11.

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Background. Anterior cruciate ligament (ACL) injuries are prevalent among younger demographics due to sportsrelated incidents, contributing to knee joint instability. Current anterior cruciate ligament reconstruction (ACLR) involves either debriding the stump (standard) or preserving the stump (stump-preserving), which retains the vascular network and mechanoreceptors in the tibial stump, aiming to improve postoperative outcomes. The autologous hamstring tendon graft is the most used, providing a higher maximum load to failure than bonepatellar tendon-bone grafts. Objective. This meta-analysis

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35

Lammertink, Imme, Paul Boersma, Frank Wijnen, and Judith Rispens. "Statistical Learning in Specific Language Impairment: A Meta-Analysis." Journal of Speech, Language, and Hearing Research 60, no. 12 (2017): 3474–86. http://dx.doi.org/10.1044/2017_jslhr-l-16-0439.

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36

FUJIMI, Toshio, Tatsuhito KONO, Hirokazu TATANO, and Ryuji KAKIMOTO. "META-ANALYSIS ON VALUE OF STATISTICAL LIFE IN JAPAN." Japanese Journal of JSCE 79, no. 20 (2023): n/a. http://dx.doi.org/10.2208/jscejj.23-20008.

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37

Shannon, Harry. "A statistical note on Karl Pearson’s 1904 meta-analysis." Journal of the Royal Society of Medicine 109, no. 8 (2016): 310–11. http://dx.doi.org/10.1177/0141076816659003.

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38

West, Robert R. "A Look at the Statistical Overview (or Meta-Analysis)." Journal of the Royal College of Physicians of London 27, no. 2 (1993): 111–15. https://doi.org/10.1016/s0035-8819(25)01007-4.

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39

Schmidt, Frank L. "Statistical and measurement pitfalls in the use of meta-regression in meta-analysis." Career Development International 22, no. 5 (2017): 469–76. http://dx.doi.org/10.1108/cdi-08-2017-0136.

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Purpose Meta-regression is widely used and misused today in meta-analyses in psychology, organizational behavior, marketing, management, and other social sciences, as an approach to the identification and calibration of moderators, with most users being unaware of serious problems in its use. The purpose of this paper is to describe nine serious methodological problems that plague applications of meta-regression. Design/methodology/approach This paper is methodological in nature and is based on well-established principles of measurement and statistics. These principles are used to illuminate t

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40

Costafreda, Sergi G. "Parametric coordinate-based meta-analysis: Valid effect size meta-analysis of studies with differing statistical thresholds." Journal of Neuroscience Methods 210, no. 2 (2012): 291–300. http://dx.doi.org/10.1016/j.jneumeth.2012.07.016.

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41

Polanin, Joshua R., Emily A. Hennessy, and Emily E. Tanner-Smith. "A Review of Meta-Analysis Packages in R." Journal of Educational and Behavioral Statistics 42, no. 2 (2016): 206–42. http://dx.doi.org/10.3102/1076998616674315.

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Meta-analysis is a statistical technique that allows an analyst to synthesize effect sizes from multiple primary studies. To estimate meta-analysis models, the open-source statistical environment R is quickly becoming a popular choice. The meta-analytic community has contributed to this growth by developing numerous packages specific to meta-analysis. The purpose of this study is to locate all publicly available meta-analytic R packages. We located 63 packages via a comprehensive online search. To help elucidate these functionalities to the field, we describe each of the packages, recommend ap

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42

Engels, Eric A., Christopher H. Schmid, Norma Terrin, Ingram Olkin, and Joseph Lau. "Heterogeneity and statistical significance in meta-analysis: an empirical study of 125 meta-analyses." Statistics in Medicine 19, no. 13 (2000): 1707–28. http://dx.doi.org/10.1002/1097-0258(20000715)19:13<1707::aid-sim491>3.0.co;2-p.

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43

Stewart, Gavin. "Meta-analysis in applied ecology." Biology Letters 6, no. 1 (2009): 78–81. http://dx.doi.org/10.1098/rsbl.2009.0546.

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This overview examines research synthesis in applied ecology and conservation. Vote counting and pooling unweighted averages are widespread despite the superiority of syntheses based on weighted combination of effects. Such analyses allow exploration of methodological uncertainty in addition to consistency of effects across species, space and time, but exploring heterogeneity remains controversial. Meta-analyses are required to generalize in ecology, and to inform evidence-based decision-making, but the more sophisticated statistical techniques and registers of research used in other disciplin

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44

Attanasio, Massimo, Fabio Aiello, and Fabio Tinè. "A statistical method for removing unbalanced trials with multiple covariates in meta-analysis." PLOS ONE 18, no. 12 (2023): e0295332. http://dx.doi.org/10.1371/journal.pone.0295332.

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In meta-analysis literature, there are several checklists describing the procedures necessary to evaluate studies from a qualitative point of view, whereas preliminary quantitative and statistical investigations on the “combinability” of trials have been neglected. Covariate balance is an important prerequisite to conduct meta-analysis. We propose a method to identify unbalanced trials with respect to a set of covariates, in presence of covariate imbalance, namely when the randomized controlled trials generate a meta-sample that cannot satisfy the requisite of randomization/combinability in me

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45

Ganduboina, Rohit, Palak Dutta, Shubadarshini Pawar, and Indraneil Mukherjee. "Meta-Suite: An innovative app for interactive, accessible, and transparent meta-analysis using R-Shiny." Impact Surgery 1, no. 5 (2024): 195–98. http://dx.doi.org/10.62463/surgery.84.

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Introduction: Meta-analysis is a powerful model for combining findings from multiple studies on a topic. Due to the growing complexity and amount of data in the digital age, research requires user-friendly tools for complex data analysis. This IDEAL phase2a study introduces Meta-Suite, which aims to simplify statistical analysis for meta-analysis with R. Methods: Meta-Suite was developed with R and Shiny to provide an intuitive General User Interface (GUI) for meta-analyses. It combines various R programs, such as meta, metasens, and metafor, and provides tools for data visualization, risk of

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46

Cafri, Guy, Jeffrey D. Kromrey, and Michael T. Brannick. "A SAS macro for statistical power calculations in meta-analysis." Behavior Research Methods 41, no. 1 (2009): 35–46. http://dx.doi.org/10.3758/brm.41.1.35.

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47

Abrami, Philip C., and Robert M. Bernard. "Statistical control versus classification of study quality in meta-analysis." Effective Education 4, no. 1 (2012): 43–72. http://dx.doi.org/10.1080/19415532.2012.761889.

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48

Donner, A., G. Piaggio, and J. Villar. "Statistical methods for the meta-analysis of cluster randomization trials." Statistical Methods in Medical Research 10, no. 5 (2001): 325–38. http://dx.doi.org/10.1191/096228001680678322.

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49

Donner, Allan, Gilda Piaggio, and José Villar. "Statistical methods for the meta-analysis of cluster randomization trials." Statistical Methods in Medical Research 10, no. 5 (2001): 325–38. http://dx.doi.org/10.1177/096228020101000502.

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50

Biggio, Battista, Giorgio Fumera, Gian Luca Marcialis, and Fabio Roli. "Statistical Meta-Analysis of Presentation Attacks for Secure Multibiometric Systems." IEEE Transactions on Pattern Analysis and Machine Intelligence 39, no. 3 (2017): 561–75. http://dx.doi.org/10.1109/tpami.2016.2558154.

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