The reproducibility crisis is not new in academic community. In order to substantiate it, the cancer researchers tried to reproduce the studies published in high ranking scientific journals, but they only succeeded to reproduce only half of the studies. This leads to lots of debates and controversies around particular theories.
One of the solutions here is to conduct a meta-analysis. Statistical analysis can help you in getting conclusion from the existing data, giving response to the unaddressed questions, constructing new hypnosis and resolving debates over a specific research question.
What is Meta-analysis?
“The statistical analysis of a large collection of analysis results from individual studies for the purpose of integrating the findings.”
Combing all the individual studies in a big study and analyzing it statistically is a way to gather all data relating to a particular question. This increases the sample size, considers more variables and analyses the data more effectively.
The Significance of Meta-analysis
To reach the conclusion is difficult when the literature is contradictory. You should be able to comprehend why the results are contradictory by comparing the whole text. A meta-analysis can resolve the related conflicting debates without repetition and resource-consuming tests in the lab. For instance, when you need a treatment regime for a clinical trial, a meta-analysis of the whole studies can tell you which treatment method has been more successful. Meta-analysis is useful for all researches and researchers often give reference to them.
Does a Meta-analysis Always Resolve the Conflicts?
A properly conducted meta-analysis takes all the facts and variables and related studies into consideration, thus you can trust the conclusions. Yet, it is not as easy as it seems. Different questions about the conducted studies in the meta-analysis should be answered. Such as:
- Are the study results valid?
- Are the variables comparable between the studies? These are usually differences in study participants, interference and results, clinical diversity and study design.
- Does one of the data sets bias the results.
For example, meta-analysis was not able to resolve the debates over the problem that whether the violent video games result in the rise of aggression among teenagers. Studies conducted on both sides of the debate resulted in conflicting conclusion. Perhaps the questions asked in the analysis were not right ones. Consequently, the meta-analysis gave rise to the conflicts rather than diminish them.
Minimizing Too Much Freedom of Researchers
If two or more researchers do the same meta-analysis, they should reach to the same conclusions with the same data sets. The best approach is to decide on the research criteria before determining which studies to include in the analysis. It is important to include failed studies in the meta-analysis. If you overlook a study this will affect the results. This is difficult because journals tend to publish positive studies more than negative ones. Some of the stages of the conferences, graduate dissertations and clinical trial registers contain the unpublished data. Generally, the meta-analysis can show a bigger picture which cannot be determined in a small study.