On the other hand, setting almost unattainable standards for inclusion can leave the meta-study with too small a sample size to be statistically relevant. Just one erroneous or poorly conducted study can place the results of the entire meta-analysis at risk. It’s important to pre-select the studies carefully, ensuring that all the research used is appropriate and of sufficient quality to be used. The researcher compiling the data must also make sure that all research is quantitative, rather than qualitative, and that the data is comparable across the various research programs, allowing a genuine statistical analysis. If the meta-study is restricted to research with positive results, then the validity of the entire endeavor is compromised. Research generating results that don’t reject null hypotheses may tend to remain unpublished, or risk not being entered into a database.
The main problem is the potential for publication bias and skewed data. There are nevertheless disadvantages to meta-analysis, of which a researcher must be aware before relying on the data and statistics it generates. Perhaps best of all, meta-studies are economical and allow research funds to be diverted elsewhere. As papers can often take many months to be physically published, instant computer records ensure that other researchers are always aware of the latest work and results in the field.Ī meta-study allows a much wider net to be cast than a traditional literature review, and is excellent for highlighting correlations and links between studies that may not be readily apparent as well as ensuring that the compiler does not subconsciously infer correlations that do not exist. Meta-analysis also ensures there is no unnecessary repeat research and allows researchers to pool resources and compare methods. The effects of error or bias in studies are kept in check. When professionals working in parallel can upload their results and access all known data on a topic, there is a built-in quality control. This allows them to conduct meaningful statistical analyses when a small local sample would have told them nothing about the disease. As we make technological developments in computational power, new database programs have made the process even easier.įor rare medical conditions, meta-analysis allows researchers to collect data from further afield than would be possible for one research group. But meta-analysis gives access to possibly more data than that team could produce in a lifetime, and allows them to condense it in useful ways. A single research team can reasonably only output so much data in a given time. Meta-analysis is an excellent way of simplifying the complexity of research.
0 kommentar(er)
