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Showing 1 to 15 of 93 results Save | Export
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Rrita Zejnullahi; Larry V. Hedges – Research Synthesis Methods, 2024
Conventional random-effects models in meta-analysis rely on large sample approximations instead of exact small sample results. While random-effects methods produce efficient estimates and confidence intervals for the summary effect have correct coverage when the number of studies is sufficiently large, we demonstrate that conventional methods…
Descriptors: Robustness (Statistics), Meta Analysis, Sample Size, Computation
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Jansen, Katrin; Holling, Heinz – Research Synthesis Methods, 2023
In meta-analyses of rare events, it can be challenging to obtain a reliable estimate of the pooled effect, in particular when the meta-analysis is based on a small number of studies. Recent simulation studies have shown that the beta-binomial model is a promising candidate in this situation, but have thus far only investigated its performance in a…
Descriptors: Bayesian Statistics, Meta Analysis, Probability, Simulation
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van Aert, Robbie C. M. – Research Synthesis Methods, 2023
The partial correlation coefficient (PCC) is used to quantify the linear relationship between two variables while taking into account/controlling for other variables. Researchers frequently synthesize PCCs in a meta-analysis, but two of the assumptions of the common equal-effect and random-effects meta-analysis model are by definition violated.…
Descriptors: Correlation, Meta Analysis, Sampling, Simulation
Timothy Scott Holcomb – ProQuest LLC, 2022
In this study, the performance of the Lambda Coefficient of Rater-Mediated Agreement was evaluated with other chance-corrected agreement coefficients. Lambda is grounded in rater-mediated assessment theory and was developed as an alternative to Kappa (Cohen, 1960) and other chance-corrected agreement coefficients. Lambda has two variations, a…
Descriptors: Evaluation Methods, Rating Scales, Simulation, Robustness (Statistics)
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Cheng, David; Tchetgen, Eric Tchetgen; Signorovitch, James – Research Synthesis Methods, 2023
Matching-adjusted indirect comparison (MAIC) enables indirect comparisons of interventions across separate studies when individual patient-level data (IPD) are available for only one study. Due to its similarity with propensity score weighting, it has been speculated that MAIC can be combined with outcome regression models in the spirit of…
Descriptors: Comparative Analysis, Robustness (Statistics), Intervention, Patients
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Lim, Hwanggyu; Choe, Edison M.; Han, Kyung T. – Journal of Educational Measurement, 2022
Differential item functioning (DIF) of test items should be evaluated using practical methods that can produce accurate and useful results. Among a plethora of DIF detection techniques, we introduce the new "Residual DIF" (RDIF) framework, which stands out for its accessibility without sacrificing efficacy. This framework consists of…
Descriptors: Test Items, Item Response Theory, Identification, Robustness (Statistics)
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Manapat, Patrick D.; Edwards, Michael C. – Educational and Psychological Measurement, 2022
When fitting unidimensional item response theory (IRT) models, the population distribution of the latent trait ([theta]) is often assumed to be normally distributed. However, some psychological theories would suggest a nonnormal [theta]. For example, some clinical traits (e.g., alcoholism, depression) are believed to follow a positively skewed…
Descriptors: Robustness (Statistics), Computational Linguistics, Item Response Theory, Psychological Patterns
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Huang, Qi; Bolt, Daniel M. – Educational and Psychological Measurement, 2023
Previous studies have demonstrated evidence of latent skill continuity even in tests intentionally designed for measurement of binary skills. In addition, the assumption of binary skills when continuity is present has been shown to potentially create a lack of invariance in item and latent ability parameters that may undermine applications. In…
Descriptors: Item Response Theory, Test Items, Skill Development, Robustness (Statistics)
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Ranger, Jochen; Kuhn, Jörg-Tobias; Wolgast, Anett – Journal of Educational Measurement, 2021
Van der Linden's hierarchical model for responses and response times can be used in order to infer the ability and mental speed of test takers from their responses and response times in an educational test. A standard approach for this is maximum likelihood estimation. In real-world applications, the data of some test takers might be partly…
Descriptors: Models, Reaction Time, Item Response Theory, Tests
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Hartwig, Fernando P.; Davey Smith, George; Schmidt, Amand F.; Sterne, Jonathan A. C.; Higgins, Julian P. T.; Bowden, Jack – Research Synthesis Methods, 2020
Meta-analyses based on systematic literature reviews are commonly used to obtain a quantitative summary of the available evidence on a given topic. However, the reliability of any meta-analysis is constrained by that of its constituent studies. One major limitation is the possibility of small-study effects, when estimates from smaller and larger…
Descriptors: Meta Analysis, Research Methodology, Effect Size, Robustness (Statistics)
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Bogaert, Jasper; Loh, Wen Wei; Rosseel, Yves – Educational and Psychological Measurement, 2023
Factor score regression (FSR) is widely used as a convenient alternative to traditional structural equation modeling (SEM) for assessing structural relations between latent variables. But when latent variables are simply replaced by factor scores, biases in the structural parameter estimates often have to be corrected, due to the measurement error…
Descriptors: Factor Analysis, Regression (Statistics), Structural Equation Models, Error of Measurement
Clark, D. Angus; Nuttall, Amy K.; Bowles, Ryan P. – International Journal of Behavioral Development, 2021
Hybrid autoregressive-latent growth structural equation models for longitudinal data represent a synthesis of the autoregressive and latent growth modeling frameworks. Although these models are conceptually powerful, in practice they may struggle to separate autoregressive and growth-related processes during estimation. This confounding of change…
Descriptors: Structural Equation Models, Longitudinal Studies, Risk, Accuracy
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Waterbury, Glenn Thomas; DeMars, Christine E. – Journal of Experimental Education, 2019
There is a need for effect sizes that are readily interpretable by a broad audience. One index that might fill this need is [pi], which represents the proportion of scores in one group that exceed the mean of another group. The robustness of estimates of [pi] to violations of normality had not been explored. Using simulated data, three estimates…
Descriptors: Effect Size, Robustness (Statistics), Simulation, Research Methodology
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Kangasrääsiö, Antti; Jokinen, Jussi P. P.; Oulasvirta, Antti; Howes, Andrew; Kaski, Samuel – Cognitive Science, 2019
This paper addresses a common challenge with computational cognitive models: identifying parameter values that are both theoretically plausible and generate predictions that match well with empirical data. While computational models can offer deep explanations of cognition, they are computationally complex and often out of reach of traditional…
Descriptors: Inferences, Computation, Cognitive Processes, Models
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Lu, Ru; Guo, Hongwen; Dorans, Neil J. – ETS Research Report Series, 2021
Two families of analysis methods can be used for differential item functioning (DIF) analysis. One family is DIF analysis based on observed scores, such as the Mantel-Haenszel (MH) and the standardized proportion-correct metric for DIF procedures; the other is analysis based on latent ability, in which the statistic is a measure of departure from…
Descriptors: Robustness (Statistics), Weighted Scores, Test Items, Item Analysis
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