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Landan Zhang; Dan Jackson – Research Synthesis Methods, 2024
A recent paper proposed an alternative weighting scheme when performing matching-adjusted indirect comparisons. This alternative approach follows the conventional one in matching the covariate means across two studies but differs in that it maximizes the effective sample size when doing so. The appendix of this paper showed, assuming there is one…
Descriptors: Comparative Analysis, Medical Research, Sample Size, Research Methodology
Andres Jung; Tobias Braun; Susan Armijo-Olivo; Dimitris Challoumas; Kerstin Luedtke – Research Synthesis Methods, 2024
External validity is an important parameter that needs to be considered for decision making in health research, but no widely accepted measurement tool for the assessment of external validity of randomized controlled trials (RCTs) exists. One of the most limiting factors for creating such a tool is probably the substantial heterogeneity and lack…
Descriptors: Randomized Controlled Trials, Validity, Delphi Technique, Definitions
Van Lissa, Caspar J.; van Erp, Sara; Clapper, Eli-Boaz – Research Synthesis Methods, 2023
When meta-analyzing heterogeneous bodies of literature, meta-regression can be used to account for potentially relevant between-studies differences. A key challenge is that the number of candidate moderators is often high relative to the number of studies. This introduces risks of overfitting, spurious results, and model non-convergence. To…
Descriptors: Bayesian Statistics, Regression (Statistics), Maximum Likelihood Statistics, Meta Analysis
Bakbergenuly, Ilyas; Hoaglin, David C.; Kulinskaya, Elena – Research Synthesis Methods, 2020
In random-effects meta-analysis the between-study variance ([tau][superscript 2]) has a key role in assessing heterogeneity of study-level estimates and combining them to estimate an overall effect. For odds ratios the most common methods suffer from bias in estimating [tau][superscript 2] and the overall effect and produce confidence intervals…
Descriptors: Meta Analysis, Statistical Bias, Intervals, Sample Size
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
Kneale, Dylan; Thomas, James; O'Mara-Eves, Alison; Wiggins, Richard – Research Synthesis Methods, 2019
This paper critically explores how survey and routinely collected data could aid in assessing the generalisability of public health evidence. We propose developing approaches that could be employed in understanding the relevance of public health evidence, and investigate ways of producing meta-analytic estimates tailored to reflect local…
Descriptors: Public Health, Decision Making, Generalization, Evidence
Hong, Hwanhee; Chu, Haitao; Zhang, Jing; Carlin, Bradley P. – Research Synthesis Methods, 2016
Bayesian statistical approaches to mixed treatment comparisons (MTCs) are becoming more popular because of their flexibility and interpretability. Many randomized clinical trials report multiple outcomes with possible inherent correlations. Moreover, MTC data are typically sparse (although richer than standard meta-analysis, comparing only two…
Descriptors: Bayesian Statistics, Meta Analysis, Outcomes of Treatment, Comparative Analysis

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