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Veroniki, Areti Angeliki; Jackson, Dan; Bender, Ralf; Kuss, Oliver; Langan, Dean; Higgins, Julian P. T.; Knapp, Guido; Salanti, Georgia – Research Synthesis Methods, 2019
Meta-analyses are an important tool within systematic reviews to estimate the overall effect size and its confidence interval for an outcome of interest. If heterogeneity between the results of the relevant studies is anticipated, then a random-effects model is often preferred for analysis. In this model, a prediction interval for the true effect…
Descriptors: Meta Analysis, Effect Size, Simulation, Comparative Analysis
Hoyer, Annika; Kuss, Oliver – Research Synthesis Methods, 2020
Diagnostic accuracy studies often evaluate diagnostic tests at several threshold values, aiming to make recommendations on optimal thresholds for use in practice. Methods for meta-analysis of full receiver operating characteristic (ROC) curves have been proposed but still have deficiencies. We recently proposed a parametric approach that is based…
Descriptors: Diagnostic Tests, Research Methodology, Accuracy, Meta Analysis
Bender, Ralf; Friede, Tim; Koch, Armin; Kuss, Oliver; Schlattmann, Peter; Schwarzer, Guido; Skipka, Guido – Research Synthesis Methods, 2018
In systematic reviews, meta-analyses are routinely applied to summarize the results of the relevant studies for a specific research question. If one can assume that in all studies the same true effect is estimated, the application of a meta-analysis with common effect (commonly referred to as fixed-effect meta-analysis) is adequate. If…
Descriptors: Evidence, Synthesis, Meta Analysis, Research Problems
Hoyer, Annika; Kuss, Oliver – Research Synthesis Methods, 2019
Diagnostic test accuracy studies frequently report on sensitivities and specificities for more than one threshold of the diagnostic test under study. Although it is obvious that the information from all thresholds should be used for a meta-analysis, in practice, frequently, only a single pair of sensitivity and specificity is selected. To overcome…
Descriptors: Meta Analysis, Diagnostic Tests, Correlation, Intervals
Mathes, Tim; Kuss, Oliver – Research Synthesis Methods, 2018
Meta-analyses often include only a small number of studies ([less than or equal to]5). Estimating between-study heterogeneity is difficult in this situation. An inaccurate estimation of heterogeneity can result in biased effect estimates and too narrow confidence intervals. The beta-binominal model has shown good statistical properties for…
Descriptors: Comparative Analysis, Meta Analysis, Probability, Statistical Analysis
Hoyer, Annika; Hirt, Stefan; Kuss, Oliver – Research Synthesis Methods, 2018
Systematic reviews and meta-analyses are the cornerstones of evidence-based medicine and inform treatment, diagnosis, or prevention of individual patients as well as policy decisions in health care. Statistical methods for the meta-analysis of intervention studies are well established today. Meta-analysis for diagnostic accuracy trials has also…
Descriptors: Medicine, Evidence Based Practice, Research Methodology, Meta Analysis
Veroniki, Areti Angeliki; Jackson, Dan; Viechtbauer, Wolfgang; Bender, Ralf; Bowden, Jack; Knapp, Guido; Kuss, Oliver; Higgins, Julian P. T.; Langan, Dean; Salanti, Georgia – Research Synthesis Methods, 2016
Meta-analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between-study variability, which is typically modelled using a between-study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between-study variance,…
Descriptors: Meta Analysis, Methods, Computation, Simulation