Publication Date
In 2025 | 2 |
Since 2024 | 3 |
Since 2021 (last 5 years) | 13 |
Descriptor
Error of Measurement | 13 |
Generalizability Theory | 13 |
Scores | 4 |
Test Reliability | 4 |
Monte Carlo Methods | 3 |
Structural Equation Models | 3 |
Computation | 2 |
Design | 2 |
Inferences | 2 |
Interrater Reliability | 2 |
Item Response Theory | 2 |
More ▼ |
Source
Author
Aksu, Gökhan | 1 |
Almehrizi, Rashid S. | 1 |
Andrea L. B. Ford | 1 |
Brendan A. Schuetze | 1 |
Custer, Michael | 1 |
Daniel McNeish | 1 |
DiStefano, Christine | 1 |
Edelman, Amanda | 1 |
Eser, Mehmet Taha | 1 |
Hayward, Charles N. | 1 |
Hong, Hyeri | 1 |
More ▼ |
Publication Type
Reports - Research | 13 |
Journal Articles | 11 |
Speeches/Meeting Papers | 1 |
Education Level
Junior High Schools | 2 |
Middle Schools | 2 |
Secondary Education | 2 |
Early Childhood Education | 1 |
Elementary Education | 1 |
Grade 8 | 1 |
Higher Education | 1 |
Postsecondary Education | 1 |
Preschool Education | 1 |
Audience
Location
Norway | 1 |
Laws, Policies, & Programs
Assessments and Surveys
Big Five Inventory | 1 |
What Works Clearinghouse Rating
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
Daniel McNeish; Melissa G. Wolf – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Despite the popularity of traditional fit index cutoffs like RMSEA [less than or equal to] 0.06 and CFI [greater than or equal to] 0.95, several studies have noted issues with overgeneralizing traditional cutoffs. Computational methods have been proposed to avoid overgeneralization by deriving cutoffs specifically tailored to the characteristics…
Descriptors: Structural Equation Models, Cutting Scores, Generalizability Theory, Error of Measurement
Vispoel, Walter P.; Lee, Hyeryung; Xu, Guanlan; Hong, Hyeri – Journal of Experimental Education, 2023
Although generalizability theory (GT) designs have traditionally been analyzed within an ANOVA framework, identical results can be obtained with structural equation models (SEMs) but extended to represent multiple sources of both systematic and measurement error variance, include estimation methods less likely to produce negative variance…
Descriptors: Generalizability Theory, Structural Equation Models, Programming Languages, Scores
Walter P. Vispoel; Hyeri Hong; Hyeryung Lee; Terrence D. Jorgensen – Applied Measurement in Education, 2023
We illustrate how to analyze complete generalizability theory (GT) designs using structural equation modeling software ("lavaan" in R), compare results to those obtained from numerous ANOVA-based packages, and apply those results in practical ways using data obtained from a large sample of respondents, who completed the Self-Perception…
Descriptors: Generalizability Theory, Design, Structural Equation Models, Error of Measurement
Comparison of the Results of the Generalizability Theory with the Inter-Rater Agreement Coefficients
Eser, Mehmet Taha; Aksu, Gökhan – International Journal of Curriculum and Instruction, 2022
The agreement between raters is examined within the scope of the concept of "inter-rater reliability". Although there are clear definitions of the concepts of agreement between raters and reliability between raters, there is no clear information about the conditions under which agreement and reliability level methods are appropriate to…
Descriptors: Generalizability Theory, Interrater Reliability, Evaluation Methods, Test Theory
Almehrizi, Rashid S. – Journal of Educational Measurement, 2021
Estimates of various variance components, universe score variance, measurement error variances, and generalizability coefficients, like all statistics, are subject to sampling variability, particularly in small samples. Such variability is quantified traditionally through estimated standard errors and/or confidence intervals. The paper derived new…
Descriptors: Error of Measurement, Statistics, Design, Generalizability Theory
Sample Size and Item Parameter Estimation Precision When Utilizing the Masters' Partial Credit Model
Custer, Michael; Kim, Jongpil – Online Submission, 2023
This study utilizes an analysis of diminishing returns to examine the relationship between sample size and item parameter estimation precision when utilizing the Masters' Partial Credit Model for polytomous items. Item data from the standardization of the Batelle Developmental Inventory, 3rd Edition were used. Each item was scored with a…
Descriptors: Sample Size, Item Response Theory, Test Items, Computation
Paul T. von Hippel; Brendan A. Schuetze – Annenberg Institute for School Reform at Brown University, 2025
Researchers across many fields have called for greater attention to heterogeneity of treatment effects--shifting focus from the average effect to variation in effects between different treatments, studies, or subgroups. True heterogeneity is important, but many reports of heterogeneity have proved to be false, non-replicable, or exaggerated. In…
Descriptors: Educational Research, Replication (Evaluation), Generalizability Theory, Inferences
Weston, Timothy J.; Hayward, Charles N.; Laursen, Sandra L. – American Journal of Evaluation, 2021
Observations are widely used in research and evaluation to characterize teaching and learning activities. Because conducting observations is typically resource intensive, it is important that inferences from observation data are made confidently. While attention focuses on interrater reliability, the reliability of a single-class measure over the…
Descriptors: Generalizability Theory, Observation, Inferences, Social Science Research
Andrea L. B. Ford; Marianne Elmquist; LeAnne D. Johnson; Jon Tapp – Journal of Speech, Language, and Hearing Research, 2025
Purpose: Estimating the sequential associations between educators' and children's talk during language learning interactions requires careful consideration of factors that may impact measurement stability and resultant inferences. This research note will describe a preliminary study that used generalizability theory to understand the contribution…
Descriptors: Preschool Children, Preschool Curriculum, Preschool Education, Preschool Teachers
Huebner, Alan; Skar, Gustaf B. – Practical Assessment, Research & Evaluation, 2021
Writing assessments often consist of students responding to multiple prompts, which are judged by more than one rater. To establish the reliability of these assessments, there exist different methods to disentangle variation due to prompts and raters, including classical test theory, Many Facet Rasch Measurement (MFRM), and Generalizability Theory…
Descriptors: Error of Measurement, Test Theory, Generalizability Theory, Item Response Theory
Simsek, Ahmet Salih – International Journal of Assessment Tools in Education, 2023
Likert-type item is the most popular response format for collecting data in social, educational, and psychological studies through scales or questionnaires. However, there is no consensus on whether parametric or non-parametric tests should be preferred when analyzing Likert-type data. This study examined the statistical power of parametric and…
Descriptors: Error of Measurement, Likert Scales, Nonparametric Statistics, Statistical Analysis
Martínez, José Felipe; Kloser, Matt; Srinivasan, Jayashri; Stecher, Brian; Edelman, Amanda – Educational and Psychological Measurement, 2022
Adoption of new instructional standards in science demands high-quality information about classroom practice. Teacher portfolios can be used to assess instructional practice and support teacher self-reflection anchored in authentic evidence from classrooms. This study investigated a new type of electronic portfolio tool that allows efficient…
Descriptors: Science Instruction, Academic Standards, Instructional Innovation, Electronic Publishing