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Meta-analysis is a statistical method that combines and synthesizes multiple studies and integrates their results. Meta-analysis increases the sample size, and in turn, the power to study the effects of interest by combining primary studies and providing a precise estimate of the effects. Data synthesized from meta-analyses are usually more beneficial than the results of narrative reviews. In a meta-analysis, the decisions are transparent, and statistical analysis yields an objective measure of the integrated quantitative evidence. The biases of narrative reviews can be limited or overcome by conducting a meta-analysis. The systematic approach and transparency in meta-analysis help to resolve conflicts and uncertainties between studies, while leading to significant conclusions. However, this method is controversial and may not always be the best tool. Moreover, meta-analysis has several shortcomings, and in some cases, it may not be appropriate. Although meta-analysis has been criticized due to its limitations, there are solutions to such problems. The aim of this review is to describe and discuss the strengths and weaknesses of meta-analysis.
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Young Ho Lee (2019) studied this question.
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