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What is Meta-analysis?
It is a quantitative approach for systematically combining results of previous studies to arrive at conclusions of a research. It is similar to cross-sectional study but here the subjects are individual studies rather than individual people. This study is mostly used for the field of medicine.
This type of study was initially used in the social sciences in 1970s but was later adopted by the field of medicine.
To sum up, this method is a statistical literature review of the magnitude of an effect in the field of medicine.
Why do we need this method in practical field of medicine?
Individual researches may be important in this field of medical science, but no matter how statistically significant they may be individually; if a lot of studies are combined together, the results become even more noteworthy. That is why it is needed to combine the effect of many studies, and produce an analysis that is far more significant than an individual research.
Let’s have an in-depth view of these four steps:
The first step in the study here is to plan the organization of your research. You can also list popular data bases which can be used for your study. Some of the popular databases that you can refer to are as follows:
It is important to remember here that these databases may be a good starting point, but you will have to refer to other sources and data to expand your study.
Once you have assembled all the data, you will have to select the right material for your research. There are many possible ways to shortlist your data:
Omit the ones that you think are irrelevant and include the important ones in your study. You can also choose previous studies based on the levels of evidences and quality of the study.
Once you have picked the right studies for analysis, you need to abstract the right data from each of the research. One easy way to abstract the data is to note down relevant information of each of the study into an excel sheet, and then combine data to arrive at a summary.
The data can be analyzed in a number of ways. You can test the effect size, variance with 95% confidence interval or test the heterogeneity.
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