Understanding random effects meta-analysis and fixed effects in meta-analysis

Meta-analysis in its basic form is meant to evaluate a singular summarized parameter from two or more studies and construct an overall majority effect estimate. But in practice, different individual studies, different experiment or study designs, different methodologies, and different populations are all different factors that can influence the final outcomes of the studies. This means that the majority of meta-analyses are actually composed of a number of different effects instead of one singular fixed effect. A solution to this problem is a meta-analysis method called random effects meta-analysis. This type of evidence synthesis allows biostatisticians to adjust for the potential random effects originating from the sources mentioned.

This is achieved statistically by considering every individual study as a random variable with potential different effects and summarizing them into one effect as a product...