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Definition
The most basic definition of meta-analysis is the synthesis of multiple studies on the same topic. The meta-analytic process identifies suitable studies, weighs their results and combines them into a single result set. The results of this process should have greater statistical weight than any of the component studies. Meta-analysis is most often performed in the field of medicine, where standardized clinical studies are common, but can be applied in any discipline where suitable studies exist.
Process Overview
The initial step in the meta-analytic process is identifying suitable studies to be combined for the desired topic. To do this, researchers find studies of a similar type, such as randomized controlled trials, from both published and unpublished sources to avoid publication bias, then discard studies that do not meet quality standards and weigh the remaining studies according to quality. Next, they enter the statistical data from each study, apply an effects model to normalize the results, and present them with visual elements such as charts or graphs.
Advantages
The results of meta-analysis carry greater statistical weight than any one study, making it a powerful tool for determining true effect size. Meta-analysis can also reveal significant variation between otherwise similar studies, and can offer a more complex look at variables and effects that influence results. For a subject where dozens of studies are published each year, a meta-analysis can put them into context and provide a wider view of the affected population.
Disadvantages
Meta-analysis can be very labor-intensive, often requiring significant effort to identify and weigh appropriate studies, especially when the studies are dissimilar, offer inadequate data or include unique variables. Using advanced statistical principles, meta-analysis requires selection of an appropriate effects model and testing to ensure the model is accurate. It's also possible that if a significant number of the component studies are poorly conducted, biased or not carefully selected, that the meta-analysis will reflect inaccurate results.