What is Meta Analysis?


Meta-analysis is a statistical technique in which the results of two or more studies are mathematically combined in order to improve the reliability of the results. Studies chosen for inclusion in a meta-analysis must be sufficiently similar in a number of characteristics in order to accurately combine their results. When the treatment effect (or effect size) is consistent from one study to the next, meta-analysis can be used to identify this common effect.  When the effect varies from one study to the next, meta-analysis may be used to identify the reason for the variation.

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Advantages of Meta Analysis

Advantages of meta-analysis (eg. over classical literature reviews, simple overall means of effect sizes etc.) include:

  • Derivation and statistical testing of overall factors / effect size parameters in related studies
  • Generalization to the population of studies
  • Ability to control for between-study variation
  • Including moderators to explain variation
  • Higher statistical power to detect an effect than in ‘n=1 sized study sample’

Weaknesses of Meta Analysis

Meta-analysis can never follow the rules of hard science, for example being double-blind, controlled, or proposing a way to falsify the theory in question. Weaknesses include:

  • Sources of bias are not controlled by the method
  • A good meta-analysis of badly designed studies will still result in bad statistics.
  • Heavy reliance on published studies, which may create exaggerated outcomes, as it is very hard to publish studies that show no significant results. (File Drawer Problem)
  • Simpson’s Paradox (two smaller studies may point in one direction, and the combination study in the opposite direction)
  • Dangers of Agenda Driven Bias: From an integrity perspective, researchers with a bias should avoid meta-analysis and use a less abuse-prone (or independent) form of research.

meta-analysisComprehensive Meta Analysis Software

Comprehensive Meta Analysis is a software application developed by some of the world’s leading meta analysis experts. Comprehensive Meta Analysis is incredibly easy to learn and use, with a clear and intuitive interface. The interactive guide will walk you through all steps in the analysis, allowing new users to be productive within minutes. With Comprehensive Meta Analysis, the logic of meta-analysis comes alive.  Use the program to help explain complex issues, such as the impact of study weights on the combined effect, the implications of heterogeneity, or the distinction between fixed effect and random effects models.

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Comprehensive Meta-Analysis will allow you to:

Work with a spreadsheet interface

Compute the treatment effect (or effect size) automatically

Perform the meta-analysis quickly and accurately

Create a high-resolution forest plot with a single click

Perform a cumulative meta-analysis

Perform a sensitivity analysis

Assess the impact of moderator variables

Work with multiple subgroups or outcomes within studies

Assess the potential impact of publication bias

Work with subsets of the data

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