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Joo, Seang-Hwane; Wang, Yan; Ferron, John; Beretvas, S. Natasha; Moeyaert, Mariola; Van Den Noortgate, Wim – Journal of Educational and Behavioral Statistics, 2022
Multiple baseline (MB) designs are becoming more prevalent in educational and behavioral research, and as they do, there is growing interest in combining effect size estimates across studies. To further refine the meta-analytic methods of estimating the effect, this study developed and compared eight alternative methods of estimating intervention…
Descriptors: Meta Analysis, Effect Size, Computation, Statistical Analysis
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Jackson, Dan; Rhodes, Kirsty; Ouwens, Mario – Research Synthesis Methods, 2021
Methods for indirect comparisons and network meta-analysis use aggregate level data from multiple studies. A very common, and closely related, scenario is where a company has individual patient data (IPD) from its own trial, but only has published aggregate data from a competitor's trial, and an indirect comparison of the treatments evaluated in…
Descriptors: Comparative Analysis, Meta Analysis, Sample Size, Statistical Analysis
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Taylor, Joseph A.; Pigott, Terri; Williams, Ryan – Educational Researcher, 2022
Toward the goal of more rapid knowledge accumulation via better meta-analyses, this article explores statistical approaches intended to increase the precision and comparability of effect sizes from education research. The featured estimate of the proposed approach is a standardized mean difference effect size whose numerator is a mean difference…
Descriptors: Statistical Analysis, Effect Size, Meta Analysis, Comparative Analysis
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Piepho, Hans-Peter; Madden, Laurence V. – Research Synthesis Methods, 2022
Network meta-analysis is a popular method to synthesize the information obtained in a systematic review of studies (e.g., randomized clinical trials) involving subsets of multiple treatments of interest. The dominant method of analysis employs within-study information on treatment contrasts and integrates this over a network of studies. One…
Descriptors: Medical Research, Meta Analysis, Networks, Drug Therapy
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Papadimitropoulou, Katerina; Stijnen, Theo; Riley, Richard D.; Dekkers, Olaf M.; Cessie, Saskia – Research Synthesis Methods, 2020
Meta-analysis of individual participant data (IPD) is considered the "gold-standard" for synthesizing clinical study evidence. However, gaining access to IPD can be a laborious task (if possible at all) and in practice only summary (aggregate) data are commonly available. In this work we focus on meta-analytic approaches of comparative…
Descriptors: Meta Analysis, Correlation, Scores, Outcomes of Treatment
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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
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Saluja, Ronak; Cheng, Sierra; delos Santos, Keemo Althea; Chan, Kelvin K. W. – Research Synthesis Methods, 2019
Objective: Various statistical methods have been developed to estimate hazard ratios (HRs) from published Kaplan-Meier (KM) curves for the purpose of performing meta-analyses. The objective of this study was to determine the reliability, accuracy, and precision of four commonly used methods by Guyot, Williamson, Parmar, and Hoyle and Henley.…
Descriptors: Meta Analysis, Reliability, Accuracy, Randomized Controlled Trials
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Cheung, Mike W.-L.; Cheung, Shu Fai – Research Synthesis Methods, 2016
Meta-analytic structural equation modeling (MASEM) combines the techniques of meta-analysis and structural equation modeling for the purpose of synthesizing correlation or covariance matrices and fitting structural equation models on the pooled correlation or covariance matrix. Both fixed-effects and random-effects models can be defined in MASEM.…
Descriptors: Statistical Analysis, Models, Meta Analysis, Structural Equation Models
Zimmerman, Kathleen N.; Pustejovsky, James E.; Ledford, Jennifer R.; Barton, Erin E.; Severini, Katherine E.; Lloyd, Blair P. – Grantee Submission, 2018
Varying methods for evaluating the outcomes of single case research designs (SCD) are currently used in reviews and meta-analyses of interventions. Quantitative effect size measures are often presented alongside visual analysis conclusions. Six measures across two classes--overlap measures (percentage non-overlapping data, improvement rate…
Descriptors: Research Design, Evaluation Methods, Synthesis, Intervention
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Mengersen, Kerrie; MacNeil, M. Aaron; Caley, M. Julian – Research Synthesis Methods, 2015
Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable…
Descriptors: Meta Analysis, Ecology, Decision Making, Statistical Analysis
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Simpson, Adrian – Journal of Education Policy, 2017
Increased attention on "what works" in education has led to an emphasis on developing policy from evidence based on comparing and combining a particular statistical summary of intervention studies: the standardised effect size. It is assumed that this statistical summary provides an estimate of the educational impact of interventions and…
Descriptors: Public Policy, Educational Policy, Effect Size, Evidence Based Practice
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Mawdsley, David; Higgins, Julian P. T.; Sutton, Alex J.; Abrams, Keith R. – Research Synthesis Methods, 2017
In meta-analysis, the random-effects model is often used to account for heterogeneity. The model assumes that heterogeneity has an additive effect on the variance of effect sizes. An alternative model, which assumes multiplicative heterogeneity, has been little used in the medical statistics community, but is widely used by particle physicists. In…
Descriptors: Databases, Meta Analysis, Goodness of Fit, Effect Size
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Faulconer, E. K.; Griffith, J. C.; Wood, B. L.; Acharyya, S.; Roberts, D. L. – Chemistry Education Research and Practice, 2018
While the equivalence between online and traditional classrooms has been well researched, very little effort has been expended to do such comparisons for college level introductory chemistry. The existing literature has only one study that investigated chemistry lectures at an entire course level as opposed to particular course components such as…
Descriptors: Online Courses, Electronic Learning, Conventional Instruction, Comparative Analysis
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Kalandadze, Tamar; Norbury, Courtenay; Naerland, Terje; Naess, Kari-Anne B. – Autism: The International Journal of Research and Practice, 2018
We present a meta-analysis of studies that compare figurative language comprehension in individuals with autism spectrum disorder and in typically developing controls who were matched based on chronological age or/and language ability. A total of 41 studies and 45 independent effect sizes were included based on predetermined inclusion criteria.…
Descriptors: Figurative Language, Reading Comprehension, Autism, Pervasive Developmental Disorders
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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
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