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Davidson, Allison; Gundlach, Ellen – International Journal of Mathematical Education in Science and Technology, 2023
A disadvantage to online clothes shopping is the inability to try on clothing to test the fit. A class project is discussed where students consult with the CEO of an online mensware clothing company to explore ways in which an online clothing customer can be assured of a superior fit by developing statistical models based on a shopper's height and…
Descriptors: Internet, Retailing, Prediction, Clothing
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Jiang, Zhehan; Raymond, Mark; DiStefano, Christine; Shi, Dexin; Liu, Ren; Sun, Junhua – Educational and Psychological Measurement, 2022
Computing confidence intervals around generalizability coefficients has long been a challenging task in generalizability theory. This is a serious practical problem because generalizability coefficients are often computed from designs where some facets have small sample sizes, and researchers have little guide regarding the trustworthiness of the…
Descriptors: Monte Carlo Methods, Intervals, Generalizability Theory, Error of Measurement
Christopher E. Shank – ProQuest LLC, 2024
This dissertation compares the performance of equivalence test (EQT) and null hypothesis test (NHT) procedures for identifying invariant and noninvariant factor loadings under a range of experimental manipulations. EQT is the statistically appropriate approach when the research goal is to find evidence of group similarity rather than group…
Descriptors: Factor Analysis, Goodness of Fit, Intervals, Comparative Analysis
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Raykov, Tenko; Marcoulides, George A. – Measurement: Interdisciplinary Research and Perspectives, 2023
This article outlines a readily applicable procedure for point and interval estimation of the population discrepancy between reliability and the popular Cronbach's coefficient alpha for unidimensional multi-component measuring instruments with uncorrelated errors, which are widely used in behavioral and social research. The method is developed…
Descriptors: Measurement, Test Reliability, Measurement Techniques, Error of Measurement
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Yuejin Zhou; Wenwu Wang; Tao Hu; Tiejun Tong; Zhonghua Liu – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Causal mediation analysis is a popular approach for investigating whether the effect of an exposure on an outcome is through a mediator to better understand the underlying causal mechanism. In recent literature, mediation analysis with multiple mediators has been proposed for continuous and dichotomous outcomes. In contrast, methods for mediation…
Descriptors: Regression (Statistics), Causal Models, Evaluation Methods, Vignettes
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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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Kulinskaya, Elena; Hoaglin, David C. – Research Synthesis Methods, 2023
For estimation of heterogeneity variance T[superscript 2] in meta-analysis of log-odds-ratio, we derive new mean- and median-unbiased point estimators and new interval estimators based on a generalized Q statistic, Q[subscript F], in which the weights depend on only the studies' effective sample sizes. We compare them with familiar estimators…
Descriptors: Q Methodology, Statistical Analysis, Meta Analysis, Intervals
Dan Soriano; Eli Ben-Michael; Peter Bickel; Avi Feller; Samuel D. Pimentel – Grantee Submission, 2023
Assessing sensitivity to unmeasured confounding is an important step in observational studies, which typically estimate effects under the assumption that all confounders are measured. In this paper, we develop a sensitivity analysis framework for balancing weights estimators, an increasingly popular approach that solves an optimization problem to…
Descriptors: Statistical Analysis, Computation, Mathematical Formulas, Monte Carlo Methods
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Paek, Insu; Lin, Zhongtian; Chalmers, Robert Philip – Educational and Psychological Measurement, 2023
To reduce the chance of Heywood cases or nonconvergence in estimating the 2PL or the 3PL model in the marginal maximum likelihood with the expectation-maximization (MML-EM) estimation method, priors for the item slope parameter in the 2PL model or for the pseudo-guessing parameter in the 3PL model can be used and the marginal maximum a posteriori…
Descriptors: Models, Item Response Theory, Test Items, Intervals
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Silva Diaz, John Alexander; Köhler, Carmen; Hartig, Johannes – Applied Measurement in Education, 2022
Testing item fit is central in item response theory (IRT) modeling, since a good fit is necessary to draw valid inferences from estimated model parameters. "Infit" and "outfit" fit statistics, widespread indices for detecting deviations from the Rasch model, are affected by data factors, such as sample size. Consequently, the…
Descriptors: Intervals, Item Response Theory, Item Analysis, Inferences
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Koçak, Duygu – Pedagogical Research, 2020
Iteration number in Monte Carlo simulation method used commonly in educational research has an effect on Item Response Theory test and item parameters. The related studies show that the number of iteration is at the discretion of the researcher. Similarly, there is no specific number suggested for the number of iteration in the related literature.…
Descriptors: Monte Carlo Methods, Item Response Theory, Educational Research, Test Items
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Seide, Svenja E.; Jensen, Katrin; Kieser, Meinhard – Research Synthesis Methods, 2020
The performance of statistical methods is often evaluated by means of simulation studies. In case of network meta-analysis of binary data, however, simulations are not currently available for many practically relevant settings. We perform a simulation study for sparse networks of trials under between-trial heterogeneity and including multi-arm…
Descriptors: Bayesian Statistics, Meta Analysis, Data Analysis, Networks
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Kim, Kyung Yong; Lee, Won-Chan – Journal of Educational Measurement, 2018
Reporting confidence intervals with test scores helps test users make important decisions about examinees by providing information about the precision of test scores. Although a variety of estimation procedures based on the binomial error model are available for computing intervals for test scores, these procedures assume that items are randomly…
Descriptors: Weighted Scores, Error of Measurement, Test Use, Decision Making
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Rubio-Aparicio, María; López-López, José Antonio; Sánchez-Meca, Julio; Marín-Martínez, Fulgencio; Viechtbauer, Wolfgang; Van den Noortgate, Wim – Research Synthesis Methods, 2018
The random-effects model, applied in most meta-analyses nowadays, typically assumes normality of the distribution of the effect parameters. The purpose of this study was to examine the performance of various random-effects methods (standard method, Hartung's method, profile likelihood method, and bootstrapping) for computing an average effect size…
Descriptors: Effect Size, Meta Analysis, Intervals, Monte Carlo Methods
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Yoder, Paul J.; Ledford, Jennifer R.; Harbison, Amy L.; Tapp, Jon T. – Journal of Early Intervention, 2018
A simulation study that used 3,000 computer-generated event streams with known behavior rates, interval durations, and session durations was conducted to test whether the main and interaction effects of true rate and interval duration affect the error level of uncorrected and Poisson-transformed (i.e., "corrected") count as estimated by…
Descriptors: Computation, Child Behavior, Early Childhood Education, Early Intervention
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