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Ferdinand Valentin Stoye; Claudia Tschammler; Oliver Kuss; Annika Hoyer – Research Synthesis Methods, 2024
The development of new statistical models for the meta-analysis of diagnostic test accuracy studies is still an ongoing field of research, especially with respect to summary receiver operating characteristic (ROC) curves. In the recently published updated version of the "Cochrane Handbook for Systematic Reviews of Diagnostic Test…
Descriptors: Diagnostic Tests, Accuracy, Barriers, Models
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Jona Lilienthal; Sibylle Sturtz; Christoph Schürmann; Matthias Maiworm; Christian Röver; Tim Friede; Ralf Bender – Research Synthesis Methods, 2024
In Bayesian random-effects meta-analysis, the use of weakly informative prior distributions is of particular benefit in cases where only a few studies are included, a situation often encountered in health technology assessment (HTA). Suggestions for empirical prior distributions are available in the literature but it is unknown whether these are…
Descriptors: Bayesian Statistics, Meta Analysis, Health Sciences, Technology
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Migliavaca, Celina Borges; Stein, Cinara; Colpani, Verônica; Barker, Timothy Hugh; Ziegelmann, Patricia Klarmann; Munn, Zachary; Falavigna, Maicon – Research Synthesis Methods, 2022
Over the last decade, there has been a 10-fold increase in the number of published systematic reviews of prevalence. In meta-analyses of prevalence, the summary estimate represents an average prevalence from included studies. This estimate is truly informative only if there is no substantial heterogeneity among the different contexts being pooled.…
Descriptors: Incidence, Meta Analysis, Statistics, Statistical Distributions
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Cao, Wenhao; Siegel, Lianne; Zhou, Jincheng; Zhu, Motao; Tong, Tiejun; Chen, Yong; Chu, Haitao – Research Synthesis Methods, 2021
A reference interval provides a basis for physicians to determine whether a measurement is typical of a healthy individual. It can be interpreted as a prediction interval for a new individual from the overall population. However, a reference interval based on a single study may not be representative of the broader population. Meta-analysis can…
Descriptors: Meta Analysis, Statistical Analysis, Intervals, Computation
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Frömke, Cornelia; Kirstein, Mathia; Zapf, Antonia – Research Synthesis Methods, 2022
The accuracy of a diagnostic test is often expressed using a pair of measures: sensitivity (proportion of test positives among all individuals with target condition) and specificity (proportion of test negatives among all individuals without target condition). If the outcome of a diagnostic test is binary, results from different studies can easily…
Descriptors: Accuracy, Diagnostic Tests, Meta Analysis, Statistical Analysis
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Noma, Hisashi; Hamura, Yasuyuki; Gosho, Masahiko; Furukawa, Toshi A. – Research Synthesis Methods, 2023
Network meta-analysis has been an essential methodology of systematic reviews for comparative effectiveness research. The restricted maximum likelihood (REML) method is one of the current standard inference methods for multivariate, contrast-based meta-analysis models, but recent studies have revealed the resultant confidence intervals of average…
Descriptors: Network Analysis, Meta Analysis, Regression (Statistics), Error of Measurement
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Riley, Richard D.; Collins, Gary S.; Hattle, Miriam; Whittle, Rebecca; Ensor, Joie – Research Synthesis Methods, 2023
Before embarking on an individual participant data meta-analysis (IPDMA) project, researchers should consider the power of their planned IPDMA conditional on the studies promising their IPD and their characteristics. Such power estimates help inform whether the IPDMA project is worth the time and funding investment, before IPD are collected. Here,…
Descriptors: Computation, Meta Analysis, Participant Characteristics, Data
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Domínguez Islas, Clara; Rice, Kenneth M. – Research Synthesis Methods, 2022
Bayesian methods seem a natural choice for combining sources of evidence in meta-analyses. However, in practice, their sensitivity to the choice of prior distribution is much less attractive, particularly for parameters describing heterogeneity. A recent non-Bayesian approach to fixed-effects meta-analysis provides novel ways to think about…
Descriptors: Bayesian Statistics, Evidence, Meta Analysis, Statistical Inference
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Kwon, Deukwoo; Reddy, Roopesh Reddy Sadashiva; Reis, Isildinha M. – Research Synthesis Methods, 2021
In meta-analysis based on continuous outcome, estimated means and corresponding standard deviations from the selected studies are key inputs to obtain a pooled estimate of the mean and its confidence interval. We often encounter the situation that these quantities are not directly reported in the literatures. Instead, other summary statistics are…
Descriptors: Meta Analysis, Computation, Bayesian Statistics, Computer Oriented Programs
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Wang, Wei-Jhih; Devine, Beth; Bansal, Aasthaa; White, H. Steve; Basu, Anirban – Research Synthesis Methods, 2021
Meta-analyzing count data can be challenging when follow-up time varies across studies. Simply pooling aggregate data over time-periods would result in biased estimates, which may erroneously inform clinical decision-making. In this study, we exploit the convolution property of the Poisson distribution to develop a likelihood for observed…
Descriptors: Meta Analysis, Data, Statistical Distributions, Computation
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Stanley, T. D.; Doucouliagos, Hristos – Research Synthesis Methods, 2023
Partial correlation coefficients are often used as effect sizes in the meta-analysis and systematic review of multiple regression analysis research results. There are two well-known formulas for the variance and thereby for the standard error (SE) of partial correlation coefficients (PCC). One is considered the "correct" variance in the…
Descriptors: Correlation, Statistical Bias, Error Patterns, Error Correction
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Kulinskaya, Elena; Hoaglin, David C.; Bakbergenuly, Ilyas; Newman, Joseph – Research Synthesis Methods, 2021
The conventional Q statistic, using estimated inverse-variance (IV) weights, underlies a variety of problems in random-effects meta-analysis. In previous work on standardized mean difference and log-odds-ratio, we found superior performance with an estimator of the overall effect whose weights use only group-level sample sizes. The Q statistic…
Descriptors: Q Methodology, Meta Analysis, Statistical Analysis, Statistical Distributions
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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
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Wang, Chia-Chun; Lee, Wen-Chung – Research Synthesis Methods, 2019
A systematic review and meta-analysis is an important step in evidence synthesis. The current paradigm for meta-analyses requires a presentation of the means under a random-effects model; however, a mean with a confidence interval provides an incomplete summary of the underlying heterogeneity in meta-analysis. Prediction intervals show the range…
Descriptors: Meta Analysis, Computation, Statistical Analysis, Prediction
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Donegan, Sarah; Dias, Sofia; Tudur-Smith, Catrin; Marinho, Valeria; Welton, Nicky J. – Research Synthesis Methods, 2018
Background: Meta-regression results must be interpreted taking into account the range of covariate values of the contributing studies. Results based on interpolation or extrapolation may be unreliable. In network meta-regression (NMR) models, which include covariates in network meta-analyses, results are estimated using direct and indirect…
Descriptors: Graphs, Networks, Meta Analysis, Regression (Statistics)
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