Abstract
Meta-analysis, a statistical procedure that integrates the results of several independent studies, plays a central role in statistical research, and a very important task in research problems and statistical significance tests. This paper discusses these principles, along with the practical steps in performing meta-analysis. It describes the issue of meta-analysis, explains what meta-analysis is, how it is done and how it can be interpreted. Some related problems such as statistical significance, effect size and power analysis are described. Examples of implementation on theoretical data would be carried. Results, conclusions, recommendations on the use of meta-analysis would be summarized.
Highlights
Sample size shouldn't be used as a criterion for including or excluding studies, because the statistical techniques used for the meta-analysis will give studies with smaller sample sizes the lower weight they deserve
Meta-analysis should be seen as structuring the processes through which a thorough review of previous research is carried out
Meta-analytic approaches have demonstrable benefits in addressing the limitations of study size, can include diverse populations, provide the opportunity to evaluate new hypotheses, and are more valuable than any single study contributing to the analysis
Summary
Well conducted meta-analyses allow a more objective appraisal of the evidence than traditional narrative reviews, provide a more precise estimate of a treatment effect, and may explain heterogeneity between the results of individual studies. Conducted meta-analyses, on the other hand, may be biased owing to exclusion of relevant studies or inclusion of inadequate studies Egger, M et al (1997) It is is a statistical technique in which the results of two or more studies are mathematically combined to see if the overall effect is significant in order to improve the reliability of the results. The use of effect sizes, has generally been limited to metaanalysis for combining and comparing estimates from different studies. Considered an evidence-based resource, meta-analysis offers the opportunity to critically evaluate and statistically combine results of comparable studies or trials. Its called heterogeneity. 3) Prediction – If there is heterogeneity (variability), we look for moderating variables that explain the variability (does the effect of X on Y differ with moderator variables?)
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