#Comprehensive meta analysis accuracy professional

The purpose of the preferred reporting Items for Systematic Reviews and Meta-Analyses (SRMA) guidelines is to aid researchers in the reporting of SRMA ( Liberati et al, 2009 Moher et al, 2010).

Systematic reviews are of special value in aggregating and synthesising the findings of many separately conducted studies, sometimes with conflicting results ( Clarke, 2007). Systematic reviews of high-quality randomised controlled trials are crucial in evidence-based medicine (EBM), as they are particularly useful for overcoming the difficulties faced by clinicians when they wish to extract and analyse dates to guide their practice. The presented protocols have been successfully tested by clinicians without meta-analysis experience. Investigators who follow the outlined methods should be able to understand the basic ideas behind the steps taken, the meaning of the meta-analysis results obtained for diagnostic and prognostic markers and the scope of questions that can be answered with Systematic Reviews and Meta-Analyses (SRMA). The paper does not attempt to serve as a comprehensive theoretical guide but instead describes one rigorous way of conducting a meta-analysis for diagnostic and prognostic markers. The aim of this paper is to enable individuals who have never performed a meta-analysis to do so from scratch. Hence, it is necessary for these users to have a simplified version of a protocol to help them to quickly conduct meta-analyses of the accuracy of diagnostic and prognostic tests. Regarding the practical application of meta-analyses for diagnostic and prognostic markers, the majority of users are clinicians and biologists, most of whom are not skilled at mathematics and computer science in particular.

#Comprehensive meta analysis accuracy professional

However, conducting such analyses requires not only a great deal of time but also an advanced professional knowledge of mathematics, statistics and computer science. Moreover, the most popular application of meta-analyses in this field may be to examine diagnostic (sensitivity and specificity) and prognostic (hazard ratio (HR) and its variance, standard error (SE) or confidence interval (CI)) test accuracy.

In evidence-based medicine (EBM), systematic reviews and meta-analyses have been widely applied in biological and medical research.