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Charlotte Z. Mann; Adam C. Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2025
Combining observational and experimental data for causal inference can improve treatment effect estimation. However, many observational data sets cannot be released due to data privacy considerations, so one researcher may not have access to both experimental and observational data. Nonetheless, a small amount of risk of disclosing sensitive…
Descriptors: Causal Models, Statistical Analysis, Privacy, Risk
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Proctor, Tanja; Zimmermann, Samuel; Seide, Svenja; Kieser, Meinhard – Research Synthesis Methods, 2022
During drug development, a biomarker is sometimes identified as separating a patient population into those with more and those with less benefit from evaluated treatments. Consequently, later studies might be targeted, while earlier ones are performed in mixed patient populations. This poses a challenge in evidence synthesis, especially if only…
Descriptors: Comparative Analysis, Meta Analysis, Patients, Medical Research
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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
Giacalone, James – ProQuest LLC, 2017
Simulation technology in healthcare education is continuously evolving but little is known about the effects of high fidelity simulation on student knowledge and skill retention or motivation. The purpose of this quantitative study was to use quasi-experimental design in a randomized controlled trial that compared the retention of knowledge and…
Descriptors: Simulation, Fidelity, Allied Health Occupations Education, Statistical Analysis
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Alam, Fahad; Boet, Sylvain; Piquette, Dominique; Lai, Anita; Perkes, Christopher P.; LeBlanc, Vicki R. – Advances in Health Sciences Education, 2016
Enhanced podcasts increase learning, but evidence is lacking on how they should be designed to optimize their effectiveness. This study assessed the impact two learning instructional design methods (mental practice and modeling), either on their own or in combination, for teaching complex cognitive medical content when incorporated into enhanced…
Descriptors: Electronic Learning, Handheld Devices, Audio Equipment, Instructional Design
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Aydin, Burak; Leite, Walter L.; Algina, James – Educational and Psychological Measurement, 2016
We investigated methods of including covariates in two-level models for cluster randomized trials to increase power to detect the treatment effect. We compared multilevel models that included either an observed cluster mean or a latent cluster mean as a covariate, as well as the effect of including Level 1 deviation scores in the model. A Monte…
Descriptors: Error of Measurement, Predictor Variables, Randomized Controlled Trials, Experimental Groups
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Buchanan, Taylor L.; Lohse, Keith R. – Measurement in Physical Education and Exercise Science, 2016
We surveyed researchers in the health and exercise sciences to explore different areas and magnitudes of bias in researchers' decision making. Participants were presented with scenarios (testing a central hypothesis with p = 0.06 or p = 0.04) in a random order and surveyed about what they would do in each scenario. Participants showed significant…
Descriptors: Researchers, Attitudes, Statistical Significance, Bias