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Sean Joo; Montserrat Valdivia; Dubravka Svetina Valdivia; Leslie Rutkowski – Journal of Educational and Behavioral Statistics, 2024
Evaluating scale comparability in international large-scale assessments depends on measurement invariance (MI). The root mean square deviation (RMSD) is a standard method for establishing MI in several programs, such as the Programme for International Student Assessment and the Programme for the International Assessment of Adult Competencies.…
Descriptors: International Assessment, Monte Carlo Methods, Statistical Studies, Error of Measurement
Nuria Real-Brioso; Eduardo Estrada; Pablo F. Cáncer – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Accelerated longitudinal designs (ALDs) provide an opportunity to capture long developmental periods in a shorter time framework using a relatively small number of assessments. Prior literature has investigated whether univariate developmental processes can be characterized with data obtained from ALDs. However, many important questions in…
Descriptors: Longitudinal Studies, Psychology, Cognitive Development, Brain Hemisphere Functions
Chalmers, R. Philip; Zheng, Guoguo – Applied Measurement in Education, 2023
This article presents generalizations of SIBTEST and crossing-SIBTEST statistics for differential item functioning (DIF) investigations involving more than two groups. After reviewing the original two-group setup for these statistics, a set of multigroup generalizations that support contrast matrices for joint tests of DIF are presented. To…
Descriptors: Test Bias, Test Items, Item Response Theory, Error of Measurement
Vembye, Mikkel Helding; Pustejovsky, James Eric; Pigott, Therese Deocampo – Journal of Educational and Behavioral Statistics, 2023
Meta-analytic models for dependent effect sizes have grown increasingly sophisticated over the last few decades, which has created challenges for a priori power calculations. We introduce power approximations for tests of average effect sizes based upon several common approaches for handling dependent effect sizes. In a Monte Carlo simulation, we…
Descriptors: Meta Analysis, Robustness (Statistics), Statistical Analysis, Models
Qi, Hongchao; Rizopoulos, Dimitris; Rosmalen, Joost – Research Synthesis Methods, 2023
The meta-analytic-predictive (MAP) approach is a Bayesian method to incorporate historical controls in new trials that aims to increase the statistical power and reduce the required sample size. Here we investigate how to calculate the sample size of the new trial when historical data is available, and the MAP approach is used in the analysis. In…
Descriptors: Sample Size, Computation, Meta Analysis, Bayesian Statistics
Rüttenauer, Tobias; Ludwig, Volker – Sociological Methods & Research, 2023
Fixed effects (FE) panel models have been used extensively in the past, as those models control for all stable heterogeneity between units. Still, the conventional FE estimator relies on the assumption of parallel trends between treated and untreated groups. It returns biased results in the presence of heterogeneous slopes or growth curves that…
Descriptors: Hierarchical Linear Modeling, Monte Carlo Methods, Statistical Bias, Computation
Joo, Seang-Hwane; Lee, Philseok – Journal of Educational Measurement, 2022
Abstract This study proposes a new Bayesian differential item functioning (DIF) detection method using posterior predictive model checking (PPMC). Item fit measures including infit, outfit, observed score distribution (OSD), and Q1 were considered as discrepancy statistics for the PPMC DIF methods. The performance of the PPMC DIF method was…
Descriptors: Test Items, Bayesian Statistics, Monte Carlo Methods, Prediction
Luke W. Miratrix – Grantee Submission, 2022
We are sometimes forced to use the Interrupted Time Series (ITS) design as an identification strategy for potential policy change, such as when we only have a single treated unit and cannot obtain comparable controls. For example, with recent county- and state-wide criminal justice reform efforts, where judicial bodies have changed bail setting…
Descriptors: Causal Models, Case Studies, Quasiexperimental Design, Monte Carlo Methods
Richa Ghevarghese – ProQuest LLC, 2022
Growth mixture modeling (GMM) is a methodological tool used to represent heterogeneity in longitudinal datasets through the identification of unobserved subgroups following qualitatively and quantitatively distinct trajectories in a population. These growth trajectories or functional forms are informed by the underlying developmental theory, are…
Descriptors: Monte Carlo Methods, Longitudinal Studies, Simulation, Growth Models
Joseph M. Kush; Elise T. Pas; Rashelle J. Musci; Catherine P. Bradshaw – Grantee Submission, 2022
Propensity score matching and weighting methods are often used in observational effectiveness studies to reduce imbalance between treated and untreated groups on a set of potential confounders. However, much of the prior methodological literature on matching and weighting has yet to examine performance for scenarios with a majority of treated…
Descriptors: Probability, Observation, Weighted Scores, Monte Carlo Methods
Roger A. Chambers – ProQuest LLC, 2022
This study aimed to observe measurement invariance between community college students and university students in response to the Community of Inquiry (CoI) Survey instrument. Most studies of the CoI survey instruments have recorded and validated the instruments considering undergraduate or graduate students. This study sought to validate and prove…
Descriptors: Community Colleges, Inquiry, Surveys, Measurement Techniques
Zazueta-Hernández, Jorge Antonio; López-Barrientos, José Daniel – Teaching Statistics: An International Journal for Teachers, 2021
This paper walks the reader through a simple mathematical characterization of the popular children's game, "Chutes and Ladders," focusing primarily on Monte Carlo simulation. The focus is then shifted to the board game "No Te Enojes" in order to analyze the implications of the introduction of strategy. The presence of strategy…
Descriptors: Games, Monte Carlo Methods, Generalization, Mathematics
Batley, Prathiba Natesan; Hedges, Larry V. – Grantee Submission, 2021
Although statistical practices to evaluate intervention effects in SCEDs have gained prominence in the recent times, models are yet to incorporate and investigate all their analytic complexities. Most of these statistical models incorporate slopes and autocorrelations both of which contribute to trend in the data. The question that arises is…
Descriptors: Bayesian Statistics, Models, Accuracy, Computation
Bang Quan Zheng; Peter M. Bentler – Structural Equation Modeling: A Multidisciplinary Journal, 2025
This paper aims to advocate for a balanced approach to model fit evaluation in structural equation modeling (SEM). The ongoing debate surrounding chi-square test statistics and fit indices has been characterized by ambiguity and controversy. Despite the acknowledged limitations of relying solely on the chi-square test, its careful application can…
Descriptors: Monte Carlo Methods, Structural Equation Models, Goodness of Fit, Robustness (Statistics)
Jang, Yoona; Hong, Sehee – Educational and Psychological Measurement, 2023
The purpose of this study was to evaluate the degree of classification quality in the basic latent class model when covariates are either included or are not included in the model. To accomplish this task, Monte Carlo simulations were conducted in which the results of models with and without a covariate were compared. Based on these simulations,…
Descriptors: Classification, Models, Prediction, Sample Size