What is meta-analysis?

Meta-analysis is a statistical analysis that combines multiple similar or related studies and makes connections between them. In other words, it is a process that integrates different research results.  According to the Mariam-Webster dictionary,

“Meta-analysis is a quantitative statistical analysis of several separate but similar experiments or studies in order to test the pooled data for statistical significance.”

Meta-analysis can be beneficial if some of the studies analyzed in the meta-analysis process lack detailed insights about the issues individually. Therefore, analyzing all these results and cross-referencing them may get a precise common result on the subject. Meta-analysis has become one of the essential techniques in healthcare and is also used in education, psychology, marketing, political science, among other fields.

Why perform a meta-analysis?

  • As mentioned above, sometimes individual researches may not be enough in theorizing about the problem.  However, all studies contain data that may be significant if checked against similar studies. Simply put, one research can provide the other with the desired insight, and collectively analyzing them may result in an accurate theory.
  • Meta-analysis is carried under mathematical rules, so it is usually more objective and less biased. It can be very helpful in getting comprehensive data about the issue if done professionally.
  • It can help figure out the multiple researches with conflicting results by organizing and analyzing them in contrast to each other.
  • The sample size is more prominent in a meta-analysis, which means a larger amount of data is available.

  Limitations of meta-analysis

  • Because it deals with multiple studies, it can be quite time-consuming depending on the number and magnitude of the individual studies.
  • Some of the studies analyzed during the process can yield unnecessary results for the entire research and waste time and resources.
  • Multiple conflicting research results may take the whole research process in the wrong direction if not correctly handled. It all depends on how skillful the researcher is.
  • We already mentioned that meta-analysis might provide deeper insights into the data if it is free of researcher bias. However, it is not always the case. A number of studies can be analyzed in a meta-analysis, so biased researchers may choose to analyze those that “meet “their expectations.

Steps in meta-analysis

  1. Make the outline of the entire process. It may change as the analysis goes, but it is essential to plan and act according to it.
  2. Decide on which type of data is useful and what should be included for analysis.
  3. Define the strategies you want to use in analyzing the individual data.
  4. Find the shared ideas and patterns among the studies that are part of the meta-analysis.
  5.  Combine the data. Sample sizes of individual studies are different; consequently, it is crucial to use a weighted average of the results before coming to a conclusion. 

A well-conducted meta-analysis covers all the individual studies that are part of the meta-analysis and looks for common findings among them. Even though it has some limitations, it is the best option in some cases because of the large sample and data size.