NotesFAQContact Us
Collection
Advanced
Search Tips
Source
Educational and Psychological…604
Audience
Researchers1
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 604 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Goretzko, David – Educational and Psychological Measurement, 2022
Determining the number of factors in exploratory factor analysis is arguably the most crucial decision a researcher faces when conducting the analysis. While several simulation studies exist that compare various so-called factor retention criteria under different data conditions, little is known about the impact of missing data on this process.…
Descriptors: Factor Analysis, Research Problems, Data, Prediction
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Park, Sung Eun; Ahn, Soyeon; Zopluoglu, Cengiz – Educational and Psychological Measurement, 2021
This study presents a new approach to synthesizing differential item functioning (DIF) effect size: First, using correlation matrices from each study, we perform a multigroup confirmatory factor analysis (MGCFA) that examines measurement invariance of a test item between two subgroups (i.e., focal and reference groups). Then we synthesize, across…
Descriptors: Item Analysis, Effect Size, Difficulty Level, Monte Carlo Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Ferrando, Pere J.; Lorenzo-Seva, Urbano – Educational and Psychological Measurement, 2021
Unit-weight sum scores (UWSSs) are routinely used as estimates of factor scores on the basis of solutions obtained with the nonlinear exploratory factor analysis (EFA) model for ordered-categorical responses. Theoretically, this practice results in a loss of information and accuracy, and is expected to lead to biased estimates. However, the…
Descriptors: Scores, Factor Analysis, Automation, Fidelity
Peer reviewed Peer reviewed
Direct linkDirect link
Bezirhan, Ummugul; von Davier, Matthias; Grabovsky, Irina – Educational and Psychological Measurement, 2021
This article presents a new approach to the analysis of how students answer tests and how they allocate resources in terms of time on task and revisiting previously answered questions. Previous research has shown that in high-stakes assessments, most test takers do not end the testing session early, but rather spend all of the time they were…
Descriptors: Response Style (Tests), Accuracy, Reaction Time, Ability
Peer reviewed Peer reviewed
Direct linkDirect link
Beauducel, André; Hilger, Norbert – Educational and Psychological Measurement, 2021
Methods for optimal factor rotation of two-facet loading matrices have recently been proposed. However, the problem of the correct number of factors to retain for rotation of two-facet loading matrices has rarely been addressed in the context of exploratory factor analysis. Most previous studies were based on the observation that two-facet loading…
Descriptors: Factor Analysis, Statistical Analysis, Correlation, Models
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Ames, Allison J.; Myers, Aaron J. – Educational and Psychological Measurement, 2021
Contamination of responses due to extreme and midpoint response style can confound the interpretation of scores, threatening the validity of inferences made from survey responses. This study incorporated person-level covariates in the multidimensional item response tree model to explain heterogeneity in response style. We include an empirical…
Descriptors: Response Style (Tests), Item Response Theory, Longitudinal Studies, Adolescents
Peer reviewed Peer reviewed
Direct linkDirect link
Liang, Xinya – Educational and Psychological Measurement, 2020
Bayesian structural equation modeling (BSEM) is a flexible tool for the exploration and estimation of sparse factor loading structures; that is, most cross-loading entries are zero and only a few important cross-loadings are nonzero. The current investigation was focused on the BSEM with small-variance normal distribution priors (BSEM-N) for both…
Descriptors: Factor Structure, Bayesian Statistics, Structural Equation Models, Goodness of Fit
Peer reviewed Peer reviewed
Direct linkDirect link
Zhou, Sherry; Huggins-Manley, Anne Corinne – Educational and Psychological Measurement, 2020
The semi-generalized partial credit model (Semi-GPCM) has been proposed as a unidimensional modeling method for handling not applicable scale responses and neutral scale responses, and it has been suggested that the model may be of use in handling missing data in scale items. The purpose of this study is to evaluate the ability of the…
Descriptors: Models, Statistical Analysis, Response Style (Tests), Test Items
Peer reviewed Peer reviewed
Direct linkDirect link
McGrath, Kathleen V.; Leighton, Elizabeth A.; Ene, Mihaela; DiStefano, Christine; Monrad, Diane M. – Educational and Psychological Measurement, 2020
Survey research frequently involves the collection of data from multiple informants. Results, however, are usually analyzed by informant group, potentially ignoring important relationships across groups. When the same construct(s) are measured, integrative data analysis (IDA) allows pooling of data from multiple sources into one data set to…
Descriptors: Educational Environment, Meta Analysis, Student Attitudes, Teacher Attitudes
Previous Page | Next Page »
Pages: 1  |  2  |  3  |  4  |  5  |  6  |  7  |  8  |  9  |  10  |  11  |  ...  |  41