Implemented meta-analysis study can be a great benefit to society
Pubrica has extensive experience in conducting meta-analysis a quantitative, formal, epidemiological study design used to systematically assess the results of previous research to derive conclusions about that body of research.
As a general principle, generating, summarizing, and understanding the best available meta analysis evidence are essential for establishing the benefits and safety of interventions. A well designed and implemented meta-analysis study can be a great benefit to society. While meta-analysis has the potential to be a powerful tool in evaluating health care treatments and interventions, there are many potential pitfalls and problems that are yet to be resolved. A poorly performed meta-analysis can perpetuate biases from ill-conceived studies or lead to false conclusions. This, in turn, can cause consumers and caregivers, who frequently access results of meta-analysis through websites and popular press, to form incorrect conclusions and can result in inappropriate medical decisions. While the idea behind combining studies to improve precision and power is straightforward, the actual implementation of the process is difficult. Those who act or react based on meta-analysis should understand the various biases that could be incorporated into a review. Examples of some potential pitfalls in meta-analysis include publication bias, pipeline bias, and English language bias. In addition, combining studies that are not similar in study design meta-analysis, population, methods of analysis or outcome definitions can lead to biases as well, which may result in spurious conclusions being drawn.
Our Meta-analysis Writing Services
Guidelines for Reporting:Moreover, a useful guide to improve reporting of systematic reviews and meta-analysis is the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-analysis) statement that replaced the QUOROM (Quality of Reporting of Meta-analysis) statement.
Detailed Literature Search: We include all relevant studies, because loss of studies can lead to bias in the study. Typically, published papers and abstracts are identified by a computerized literature search of electronic databases that can include PubMed (http://www.ncbi.nlm.nih.gov./entrez/query.fcgi), ScienceDirect (http://www.sciencedirect.com/), Scirus (http://www.scirus.com/srsapp), ISI Web of Knowledge (https://www.isiwebofknowledge.com/), Google Scholar (https://scholar.google.com/) and CENTRAL (Cochrane Central Register of Controlled Trials, (https://www.mrw.interscience.wiley.com/cochrane/cochrane_clcentral_articles_fs.htm).
Statistical Analysis:
Heterogeneity: Heterogeneity (variation in true effect sizes and in factors that might influence those effect sizes) is inherent in meta-analysis, not a problem to be solved. It includes clinical components (eg, diversity in patient populations or interventions) and statistical components (eg, random differences).
