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Showing 31 to 45 of 3,822 results Save | Export
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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
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Lee, Sooyong; Han, Suhwa; Choi, Seung W. – Educational and Psychological Measurement, 2022
Response data containing an excessive number of zeros are referred to as zero-inflated data. When differential item functioning (DIF) detection is of interest, zero-inflation can attenuate DIF effects in the total sample and lead to underdetection of DIF items. The current study presents a DIF detection procedure for response data with excess…
Descriptors: Test Bias, Monte Carlo Methods, Simulation, Models
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Cooperman, Allison W.; Weiss, David J.; Wang, Chun – Educational and Psychological Measurement, 2022
Adaptive measurement of change (AMC) is a psychometric method for measuring intra-individual change on one or more latent traits across testing occasions. Three hypothesis tests--a Z test, likelihood ratio test, and score ratio index--have demonstrated desirable statistical properties in this context, including low false positive rates and high…
Descriptors: Error of Measurement, Psychometrics, Hypothesis Testing, Simulation
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Brennan, Robert L.; Kim, Stella Y.; Lee, Won-Chan – Educational and Psychological Measurement, 2022
This article extends multivariate generalizability theory (MGT) to tests with different random-effects designs for each level of a fixed facet. There are numerous situations in which the design of a test and the resulting data structure are not definable by a single design. One example is mixed-format tests that are composed of multiple-choice and…
Descriptors: Multivariate Analysis, Generalizability Theory, Multiple Choice Tests, Test Construction
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Raykov, Tenko; DiStefano, Christine – Educational and Psychological Measurement, 2022
A latent variable modeling-based procedure is discussed that permits to readily point and interval estimate the design effect index in multilevel settings using widely circulated software. The method provides useful information about the relationship of important parameter standard errors when accounting for clustering effects relative to…
Descriptors: Hierarchical Linear Modeling, Correlation, Evaluation, Research Design
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Nagy, Gabriel; Ulitzsch, Esther – Educational and Psychological Measurement, 2022
Disengaged item responses pose a threat to the validity of the results provided by large-scale assessments. Several procedures for identifying disengaged responses on the basis of observed response times have been suggested, and item response theory (IRT) models for response engagement have been proposed. We outline that response time-based…
Descriptors: Item Response Theory, Hierarchical Linear Modeling, Predictor Variables, Classification
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Magnus, Brooke E.; Liu, Yang – Educational and Psychological Measurement, 2022
Questionnaires inquiring about psychopathology symptoms often produce data with excess zeros or the equivalent (e.g., none, never, and not at all). This type of zero inflation is especially common in nonclinical samples in which many people do not exhibit psychopathology, and if unaccounted for, can result in biased parameter estimates when…
Descriptors: Symptoms (Individual Disorders), Psychopathology, Research Methodology, Probability
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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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Cao, Chunhua; Kim, Eun Sook; Chen, Yi-Hsin; Ferron, John – Educational and Psychological Measurement, 2021
This study examined the impact of omitting covariates interaction effect on parameter estimates in multilevel multiple-indicator multiple-cause models as well as the sensitivity of fit indices to model misspecification when the between-level, within-level, or cross-level interaction effect was left out in the models. The parameter estimates…
Descriptors: Goodness of Fit, Hierarchical Linear Modeling, Computation, Models
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Son, Sookyoung; Hong, Sehee – Educational and Psychological Measurement, 2021
The purpose of this two-part study is to evaluate methods for multiple group analysis when the comparison group is at the within level with multilevel data, using a multilevel factor mixture model (ML FMM) and a multilevel multiple-indicators multiple-causes (ML MIMIC) model. The performance of these methods was evaluated integrally by a series of…
Descriptors: Hierarchical Linear Modeling, Factor Analysis, Structural Equation Models, Groups
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Wind, Stefanie A.; Ge, Yuan – Educational and Psychological Measurement, 2021
Practical constraints in rater-mediated assessments limit the availability of complete data. Instead, most scoring procedures include one or two ratings for each performance, with overlapping performances across raters or linking sets of multiple-choice items to facilitate model estimation. These incomplete scoring designs present challenges for…
Descriptors: Evaluators, Scoring, Data Collection, Design
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Rios, Joseph A. – Educational and Psychological Measurement, 2021
Low test-taking effort as a validity threat is common when examinees perceive an assessment context to have minimal personal value. Prior research has shown that in such contexts, subgroups may differ in their effort, which raises two concerns when making subgroup mean comparisons. First, it is unclear how differential effort could influence…
Descriptors: Response Style (Tests), Statistical Analysis, Measurement, Comparative Analysis
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Gorgun, Guher; Bulut, Okan – Educational and Psychological Measurement, 2021
In low-stakes assessments, some students may not reach the end of the test and leave some items unanswered due to various reasons (e.g., lack of test-taking motivation, poor time management, and test speededness). Not-reached items are often treated as incorrect or not-administered in the scoring process. However, when the proportion of…
Descriptors: Scoring, Test Items, Response Style (Tests), Mathematics Tests
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Ellis, Jules L. – Educational and Psychological Measurement, 2021
This study develops a theoretical model for the costs of an exam as a function of its duration. Two kind of costs are distinguished: (1) the costs of measurement errors and (2) the costs of the measurement. Both costs are expressed in time of the student. Based on a classical test theory model, enriched with assumptions on the context, the costs…
Descriptors: Test Length, Models, Error of Measurement, Measurement
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Montoya, Amanda K.; Edwards, Michael C. – Educational and Psychological Measurement, 2021
Model fit indices are being increasingly recommended and used to select the number of factors in an exploratory factor analysis. Growing evidence suggests that the recommended cutoff values for common model fit indices are not appropriate for use in an exploratory factor analysis context. A particularly prominent problem in scale evaluation is the…
Descriptors: Goodness of Fit, Factor Analysis, Cutting Scores, Correlation
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