Imputing the Validity of Literature Surveys in Clinical Trials
In the medical arts, the importance of review articles in journals is increasing. The primary and basic purpose of writing such a review article is to generate a readable, comprehensible synthesis of all the resources pertaining to an important topic or a current research area of interest. Although the first motivation in writing a review article is typically to promote the views of an individual or group with an interest in a given subject, the ultimate objective is to contribute data to the knowledge base of readers in a particular area of expertise. Click here more information about motorcycle helmet reviews
A.D. R. Fisher introduced the notation for a given research subject as either “confidence interval” or “effect size” and applied it to meta-analyses in his classic paper, “meta-analyses and systematic reviews: a comparison with other statistical methods”. According to him, there is a relatively small but significant relationship between study size and effect size in meta-analyses.
b. Most researchers prefer to write a good review article focusing on a single region of expertise or on a sub-field of studies. The decision to focus on a specific area is not based on the overall conclusions reached in the entire study; rather, it is based on the organizational requirements of participating authors. Thus, for a given research question, the appropriate sub-type or region of expertise can be chosen.
c. It has been argued that most meta-analyses and systematic reviews improperly infer causality between variables that are studied simultaneously. For instance, if two research report that a certain treatment is more effective than another in a placebo arm, and a third research article reports that a given set of procedures is less harmful than others when administered individually, then it is not expected that the treatments will have equivalent effects on patients with either condition. Thus, if the number of individual studies is low and the effect sizes in the groupings are large, a reviewer cannot infer from the data that the treatment is more effective than the set of procedures individually. Similarly, for a given systematic review and meta-analysis, it is inappropriate to conclude that all studies support a conclusion (albeit statistically significant) if only one out of five or ten studies draw a conclusion that the effect was not statistically significant.
Summary and Conclusion As stated above, many researchers adhere to a methodological perspective to research quality in review articles. Meta-analyses and other meta-analyses that rely on other data sources to infer causality are more likely to conclude that there is no association between a variable and its effect on prevalence. However, many systematic reviews and meta-analyses have reported pooled effect sizes of approximately zero for many causes of death, especially pediatric diseases. In addition, some systematic reviews and meta-analyses have noted that there may be a relationship between the levels of health risk and exposure, but that this relationship was not statistically significant. Thus, when investigating the validity of literature surveying, it is important to remember that all research is observational, and while causality can be proven in many cases of death due to medical conditions, causality may not be proven in all instances.