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Bartoš, František; Maier, Maximilian; Wagenmakers, Eric-Jan; Doucouliagos, Hristos; Stanley, T. D. – Research Synthesis Methods, 2023
Publication bias is a ubiquitous threat to the validity of meta-analysis and the accumulation of scientific evidence. In order to estimate and counteract the impact of publication bias, multiple methods have been developed; however, recent simulation studies have shown the methods' performance to depend on the true data generating process, and no…
Descriptors: Robustness (Statistics), Bayesian Statistics, Meta Analysis, Publications
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Huang, Ao; Komukai, Sho; Friede, Tim; Hattori, Satoshi – Research Synthesis Methods, 2021
Prospective registration of study protocols in clinical trial registries is a useful way to minimize the risk of publication bias in meta-analysis, and several clinical trial registries are available nowadays. However, they are mainly used as a tool for searching studies and information submitted to the registries has not been utilized as…
Descriptors: Publications, Bias, Meta Analysis, Selection
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Samartsidis, Pantelis; Montagna, Silvia; Laird, Angela R.; Fox, Peter T.; Johnson, Timothy D.; Nichols, Thomas E. – Research Synthesis Methods, 2020
Coordinate-based meta-analyses (CBMA) allow researchers to combine the results from multiple functional magnetic resonance imaging experiments with the goal of obtaining results that are more likely to generalize. However, the interpretation of CBMA findings can be impaired by the file drawer problem, a type of publication bias that refers to…
Descriptors: Meta Analysis, Neurology, Diagnostic Tests, Publications
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Bom, Pedro R. D.; Rachinger, Heiko – Research Synthesis Methods, 2019
Publication bias distorts the available empirical evidence and misinforms policymaking. Evidence of publication bias is mounting in virtually all fields of empirical research. This paper proposes the endogenous kink (EK) meta-regression model as a novel method of publication bias correction. The EK method fits a piecewise linear meta-regression of…
Descriptors: Bias, Publications, Models, Regression (Statistics)
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Pedder, Hugo; Boucher, Martin; Dias, Sofia; Bennetts, Margherita; Welton, Nicky J. – Research Synthesis Methods, 2020
Time-course model-based network meta-analysis (MBNMA) has been proposed as a framework to combine treatment comparisons from a network of randomized controlled trials reporting outcomes at multiple time-points. This can explain heterogeneity/inconsistency that arises by pooling studies with different follow-up times and allow inclusion of studies…
Descriptors: Simulation, Randomized Controlled Trials, Meta Analysis, Comparative Analysis
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Freeman, S. C.; Fisher, D.; Tierney, J. F.; Carpenter, J. R. – Research Synthesis Methods, 2018
Background: Stratified medicine seeks to identify patients most likely to respond to treatment. Individual participant data (IPD) network meta-analysis (NMA) models have greater power than individual trials to identify treatment-covariate interactions (TCIs). Treatment-covariate interactions contain "within" and "across" trial…
Descriptors: Medical Research, Patients, Outcomes of Treatment, Meta Analysis
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Rhodes, William – Evaluation Review, 2012
Research synthesis of evaluation findings is a multistep process. An investigator identifies a research question, acquires the relevant literature, codes findings from that literature, and analyzes the coded data to estimate the average treatment effect and its distribution in a population of interest. The process of estimating the average…
Descriptors: Social Sciences, Regression (Statistics), Meta Analysis, Models
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Steenbergen-Hu, Saiying; Cooper, Harris – Journal of Educational Psychology, 2013
In this study, we meta-analyzed empirical research of the effectiveness of intelligent tutoring systems (ITS) on K-12 students' mathematical learning. A total of 26 reports containing 34 independent samples met study inclusion criteria. The reports appeared between 1997 and 2010. The majority of included studies compared the effectiveness of ITS…
Descriptors: Meta Analysis, Intelligent Tutoring Systems, Mathematics Instruction, Mathematics Achievement
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Bosch, Holger; Steinkamp, Fiona; Boller, Emil – Psychological Bulletin, 2006
H. Bosch, F. Steinkamp, and E. Boller's (see record 2006-08436-001) meta-analysis, which demonstrated (a) a small but highly significant overall effect, (b) a small-study effect, and (c) extreme heterogeneity, has provoked widely differing responses. After considering D. B. Wilson and W. R. Shadish's (see record 2006-08436-002) and D. Radin, R.…
Descriptors: Meta Analysis, Publications, Bias, Models
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Cox, W. Miles; Fadardi, Javad Salehi; Pothos, Emmanuel M. – Psychological Bulletin, 2006
Decisions about using addictive substances are influenced by distractions by addiction-related stimuli, of which the user might be unaware. The addiction-Stroop task is a paradigm used to assess this distraction. The empirical evidence for the addiction-Stroop effect is critically reviewed, and meta-analyses of alcohol-related and smoking-related…
Descriptors: Substance Abuse, Tests, Models, Stimuli
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Strohmer, Douglas C.; Arm, Jennifer R. – Counseling Psychologist, 2006
The results of the clinical versus statistical prediction meta-analysis support the longstanding finding that statistical methods are superior to clinical methods in making predictions. In this reaction, the authors discuss the findings from the perspective of the context of discovery and the context of justification, the client model-building…
Descriptors: Meta Analysis, Prediction, Psychological Evaluation, Bias
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Viechtbauer, Wolfgang – Journal of Educational and Behavioral Statistics, 2005
The meta-analytic random effects model assumes that the variability in effect size estimates drawn from a set of studies can be decomposed into two parts: heterogeneity due to random population effects and sampling variance. In this context, the usual goal is to estimate the central tendency and the amount of heterogeneity in the population effect…
Descriptors: Bias, Meta Analysis, Models, Effect Size