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A Guide to Conducting a Meta-Analysis with Non-Independent Effect Sizes.

ABSTRACT: Conventional meta-analytic procedures assume that effect sizes are independent. When effect sizes are not independent, conclusions based on these conventional procedures can be misleading or even wrong. Traditional approaches, such as averaging the effect sizes and selecting one effect size per study, are usually used to avoid the dependence of the effect sizes. These ad-hoc approaches, however, may lead to missed opportunities to utilize all available data to address the relevant research questions. Both multivariate meta-analysis and three-level meta-analysis have been proposed to handle non-independent effect sizes. This paper gives a brief introduction to these new techniques for applied researchers. The first objective is to highlight the benefits of using these methods to address non-independent effect sizes. The second objective is to illustrate how to apply these techniques with real data in R and Mplus. Researchers may modify the sample R and Mplus code to fit their data.

SUBMITTER: Cheung MW

PROVIDER: S-EPMC6892772 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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A Guide to Conducting a Meta-Analysis with Non-Independent Effect Sizes.

Cheung Mike W-L MW

Neuropsychology review 20190824 4

Conventional meta-analytic procedures assume that effect sizes are independent. When effect sizes are not independent, conclusions based on these conventional procedures can be misleading or even wrong. Traditional approaches, such as averaging the effect sizes and selecting one effect size per study, are usually used to avoid the dependence of the effect sizes. These ad-hoc approaches, however, may lead to missed opportunities to utilize all available data to address the relevant research quest ...[more]

PMID: 31446547

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Project description:ImportanceThe definition and nature of autism have been highly debated, as exemplified by several revisions of the DSM (DSM-III, DSM-IIIR, DSM-IV, and DSM-5) criteria. There has recently been a move from a categorical view toward a spectrum-based view. These changes have been accompanied by a steady increase in the prevalence of the condition. Changes in the definition of autism that may increase heterogeneity could affect the results of autism research; specifically, a broadening of the population with autism could result in decreasing effect sizes of group comparison studies.ObjectiveTo examine the correlation between publication year and effect size of autism-control group comparisons across several domains of published autism neurocognitive research.Data sourcesThis meta-analysis investigated 11 meta-analyses obtained through a systematic search of PubMed for meta-analyses published from January 1, 1966, through January 27, 2019, using the search string autism AND (meta-analysis OR meta-analytic). The last search was conducted on January 27, 2019.Study selectionMeta-analyses were included if they tested the significance of group differences between individuals with autism and control individuals on a neurocognitive construct. Meta-analyses were only included if the tested group difference was significant and included data with a span of at least 15 years.Data extraction and synthesisData were extracted and analyzed according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline using fixed-effects models.Main outcomes and measuresEstimated slope of the correlation between publication year and effect size, controlling for differences in methods, sample size, and study quality.ResultsThe 11 meta-analyses included data from a total of 27 723 individuals. Demographic data such as sex and age were not available for the entire data set. Seven different psychological and neurologic constructs were analyzed based on data from these meta-analyses. Downward temporal trends for effect size were found for all constructs (slopes: -0.067 to -0.003), with the trend being significant in 5 of 7 cases: emotion recognition (slope: -0.028 [95% CI, -0.048 to -0.007]), theory of mind (-0.045 [95% CI, -0.066 to -0.024]), planning (-0.067 [95% CI, -0.125 to -0.009]), P3b amplitude (-0.048 [95% CI, -0.093 to -0.004]), and brain size (-0.047 [95% CI, -0.077 to -0.016]). In contrast, 3 analogous constructs in schizophrenia, a condition that is also heterogeneous but with no reported increase in prevalence, did not show a similar trend.Conclusions and relevanceThe findings suggest that differences between individuals with autism and those without the diagnosis have decreased over time and that possible changes in the definition of autism from a narrowly defined and homogenous population toward an inclusive and heterogeneous population may reduce our capacity to build mechanistic models of the condition.

Dataset Information

A Guide to Conducting a Meta-Analysis with Non-Independent Effect Sizes.

Publications

A Guide to Conducting a Meta-Analysis with Non-Independent Effect Sizes.

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