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Su, Hsu-Lin; Chen, Po-Hsi – Educational and Psychological Measurement, 2023
The multidimensional mixture data structure exists in many test (or inventory) conditions. Heterogeneity also relatively exists in populations. Still, some researchers are interested in deciding to which subpopulation a participant belongs according to the participant's factor pattern. Thus, in this study, we proposed three analysis procedures…
Descriptors: Data Analysis, Correlation, Classification, Factor Structure
Huang, Sijia; Luo, Jinwen; Cai, Li – Educational and Psychological Measurement, 2023
Random item effects item response theory (IRT) models, which treat both person and item effects as random, have received much attention for more than a decade. The random item effects approach has several advantages in many practical settings. The present study introduced an explanatory multidimensional random item effects rating scale model. The…
Descriptors: Rating Scales, Item Response Theory, Models, Test Items
Dimitrov, Dimiter M.; Atanasov, Dimitar V. – Educational and Psychological Measurement, 2022
This study offers an approach to testing for differential item functioning (DIF) in a recently developed measurement framework, referred to as "D"-scoring method (DSM). Under the proposed approach, called "P-Z" method of testing for DIF, the item response functions of two groups (reference and focal) are compared by…
Descriptors: Test Bias, Methods, Test Items, Scoring
Finch, W. Holmes – Educational and Psychological Measurement, 2023
Psychometricians have devoted much research and attention to categorical item responses, leading to the development and widespread use of item response theory for the estimation of model parameters and identification of items that do not perform in the same way for examinees from different population subgroups (e.g., differential item functioning…
Descriptors: Test Bias, Item Response Theory, Computation, Methods
Franz Classe; Christoph Kern – Educational and Psychological Measurement, 2024
We develop a "latent variable forest" (LV Forest) algorithm for the estimation of latent variable scores with one or more latent variables. LV Forest estimates unbiased latent variable scores based on "confirmatory factor analysis" (CFA) models with ordinal and/or numerical response variables. Through parametric model…
Descriptors: Algorithms, Item Response Theory, Artificial Intelligence, Factor Analysis
Raykov, Tenko; Menold, Natalja; Leer, Jane – Educational and Psychological Measurement, 2022
Two- and three-level designs in educational and psychological research can involve entire populations of Level-3 and possibly Level-2 units, such as schools and educational districts nested within a given state, or neighborhoods and counties in a state. Such a design is of increasing relevance in empirical research owing to the growing popularity…
Descriptors: Hierarchical Linear Modeling, Computation, Statistical Analysis, Research Design
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
Man, Kaiwen; Schumacker, Randall; Morell, Monica; Wang, Yurou – Educational and Psychological Measurement, 2022
While hierarchical linear modeling is often used in social science research, the assumption of normally distributed residuals at the individual and cluster levels can be violated in empirical data. Previous studies have focused on the effects of nonnormality at either lower or higher level(s) separately. However, the violation of the normality…
Descriptors: Hierarchical Linear Modeling, Statistical Distributions, Statistical Bias, Computation
Rios, Joseph A. – Educational and Psychological Measurement, 2022
The presence of rapid guessing (RG) presents a challenge to practitioners in obtaining accurate estimates of measurement properties and examinee ability. In response to this concern, researchers have utilized response times as a proxy of RG and have attempted to improve parameter estimation accuracy by filtering RG responses using popular scoring…
Descriptors: Guessing (Tests), Classification, Accuracy, Computation
Foster, Robert C. – Educational and Psychological Measurement, 2021
This article presents some equivalent forms of the common Kuder-Richardson Formula 21 and 20 estimators for nondichotomous data belonging to certain other exponential families, such as Poisson count data, exponential data, or geometric counts of trials until failure. Using the generalized framework of Foster (2020), an equation for the reliability…
Descriptors: Test Reliability, Data, Computation, Mathematical Formulas
Raykov, Tenko; Marcoulides, George A. – Educational and Psychological Measurement, 2021
The population discrepancy between unstandardized and standardized reliability of homogeneous multicomponent measuring instruments is examined. Within a latent variable modeling framework, it is shown that the standardized reliability coefficient for unidimensional scales can be markedly higher than the corresponding unstandardized reliability…
Descriptors: Test Reliability, Computation, Measures (Individuals), Research Problems
Andersson, Gustaf; Yang-Wallentin, Fan – Educational and Psychological Measurement, 2021
Factor score regression has recently received growing interest as an alternative for structural equation modeling. However, many applications are left without guidance because of the focus on normally distributed outcomes in the literature. We perform a simulation study to examine how a selection of factor scoring methods compare when estimating…
Descriptors: Regression (Statistics), Statistical Analysis, Computation, Scoring
Dimitrov, Dimiter M. – Educational and Psychological Measurement, 2022
Proposed is a new method of standard setting referred to as response vector for mastery (RVM) method. Under the RVM method, the task of panelists that participate in the standard setting process does not involve conceptualization of a borderline examinee and probability judgments as it is the case with the Angoff and bookmark methods. Also, the…
Descriptors: Standard Setting (Scoring), Cutting Scores, Computation, Mastery Learning
Edwards, Ashley A.; Joyner, Keanan J.; Schatschneider, Christopher – Educational and Psychological Measurement, 2021
The accuracy of certain internal consistency estimators have been questioned in recent years. The present study tests the accuracy of six reliability estimators (Cronbach's alpha, omega, omega hierarchical, Revelle's omega, and greatest lower bound) in 140 simulated conditions of unidimensional continuous data with uncorrelated errors with varying…
Descriptors: Reliability, Computation, Accuracy, Sample Size
Gwet, Kilem L. – Educational and Psychological Measurement, 2021
Cohen's kappa coefficient was originally proposed for two raters only, and it later extended to an arbitrarily large number of raters to become what is known as Fleiss' generalized kappa. Fleiss' generalized kappa and its large-sample variance are still widely used by researchers and were implemented in several software packages, including, among…
Descriptors: Sample Size, Statistical Analysis, Interrater Reliability, Computation