Publication Date
In 2025 | 19 |
Since 2024 | 91 |
Descriptor
Comparative Analysis | 91 |
Models | 65 |
Foreign Countries | 23 |
Teaching Methods | 18 |
Evaluation Methods | 17 |
Simulation | 13 |
Structural Equation Models | 13 |
Error of Measurement | 12 |
Prediction | 12 |
Causal Models | 11 |
Computer Software | 11 |
More ▼ |
Source
Author
Zhiyong Zhang | 3 |
Ben Kelcey | 2 |
Charlotte Z. Mann | 2 |
Fangxing Bai | 2 |
Hong Zhang | 2 |
Johann A. Gagnon-Bartsch | 2 |
Saijun Zhao | 2 |
Tenko Raykov | 2 |
Abderrahman Mouradi | 1 |
Abida Nasreen | 1 |
Adam C. Sales | 1 |
More ▼ |
Publication Type
Reports - Research | 75 |
Journal Articles | 74 |
Dissertations/Theses -… | 7 |
Reports - Evaluative | 5 |
Reports - Descriptive | 3 |
Speeches/Meeting Papers | 3 |
Information Analyses | 2 |
Tests/Questionnaires | 1 |
Education Level
Audience
Location
China | 6 |
Germany | 3 |
Florida | 2 |
Iran | 2 |
South Korea | 2 |
United Kingdom | 2 |
Delaware | 1 |
Europe | 1 |
France | 1 |
Indonesia | 1 |
Israel | 1 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
National Longitudinal Survey… | 2 |
Early Childhood Longitudinal… | 1 |
General Social Survey | 1 |
National Longitudinal Study… | 1 |
Self Description Questionnaire | 1 |
Wechsler Adult Intelligence… | 1 |
What Works Clearinghouse Rating
Kelvin T. Afolabi; Timothy R. Konold – Practical Assessment, Research & Evaluation, 2024
Exploratory structural equation (ESEM) has received increased attention in the methodological literature as a promising tool for evaluating latent variable measurement models. It overcomes many of the limitations attached to exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), while capitalizing on the benefits of each. Given…
Descriptors: Measurement Techniques, Factor Analysis, Structural Equation Models, Comparative Analysis
Jeroen D. Mulder; Kim Luijken; Bas B. L. Penning de Vries; Ellen L. Hamaker – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The use of structural equation models for causal inference from panel data is critiqued in the causal inference literature for unnecessarily relying on a large number of parametric assumptions, and alternative methods originating from the potential outcomes framework have been recommended, such as inverse probability weighting (IPW) estimation of…
Descriptors: Structural Equation Models, Time on Task, Time Management, Causal Models
Adam N. Glynn; Miguel R. Rueda; Julian Schuessler – Sociological Methods & Research, 2024
Post-instrument covariates are often included as controls in instrumental variable (IV) analyses to address a violation of the exclusion restriction. However, we show that such analyses are subject to biases unless strong assumptions hold. Using linear constant-effects models, we present asymptotic bias formulas for three estimators (with and…
Descriptors: Causal Models, Statistical Inference, Error of Measurement, Least Squares Statistics
Dae Woong Ham; Luke Miratrix – Grantee Submission, 2024
The consequence of a change in school leadership (e.g., principal turnover) on student achievement has important implications for education policy. The impact of such an event can be estimated via the popular Difference in Difference (DiD) estimator, where those schools with a turnover event are compared to a selected set of schools that did not…
Descriptors: Trend Analysis, Faculty Mobility, Academic Achievement, Principals
Emma Somer; Carl Falk; Milica Miocevic – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Factor Score Regression (FSR) is increasingly employed as an alternative to structural equation modeling (SEM) in small samples. Despite its popularity in psychology, the performance of FSR in multigroup models with small samples remains relatively unknown. The goal of this study was to examine the performance of FSR, namely Croon's correction and…
Descriptors: Scores, Structural Equation Models, Comparative Analysis, Sample Size
Martyna Daria Swiatczak; Michael Baumgartner – Sociological Methods & Research, 2025
In this paper, we investigate the conditions under which data imbalances, a common data characteristic that occurs when factor values are unevenly distributed, are problematic for the performance of Coincidence Analysis (CNA). We further examine how such imbalances relate to fragmentation and noise in data. We show that even extreme data…
Descriptors: Causal Models, Comparative Analysis, Data Analysis, Statistical Distributions
Michael C. Robbins; Zhuping Li – Field Methods, 2025
The Nolan Index (NI) is a normed, quantitative measure for comparing the degree of resemblance (similarity or dissimilarity) between free listings with an Excel program for calculating it. This article enhances that effort with the addition of an R program and additional applications. Free-list resemblance measures have been used to investigate…
Descriptors: Computation, Norm Referenced Tests, Comparative Analysis, Spreadsheets
Markus Gangl – Sociological Methods & Research, 2025
Rating scales are ubiquitous in the social sciences, yet may present practical difficulties when response formats change over time or vary across surveys. To allow researchers to pool rating data across alternative question formats, the article provides a generalization of the ordered logit model that accommodates multiple scale formats in the…
Descriptors: Rating Scales, Surveys, Responses, Models
Sohee Kim; Ki Lynn Cole – International Journal of Testing, 2025
This study conducted a comprehensive comparison of Item Response Theory (IRT) linking methods applied to a bifactor model, examining their performance on both multiple choice (MC) and mixed format tests within the common item nonequivalent group design framework. Four distinct multidimensional IRT linking approaches were explored, consisting of…
Descriptors: Item Response Theory, Comparative Analysis, Models, Item Analysis
Hongfeng Zhang; Fanbo Li; Xiaolong Chen – Journal of Educational Computing Research, 2025
This study addresses the gap in understanding graduate students' sustained engagement behavior (SEB) with generative artificial intelligence (GAI) by integrating the Technology Acceptance Model (TAM), Expectation Confirmation Theory (ECT), and Theory of Reasoned Action (TRA) into a comprehensive embedding model. It introduces the Technology…
Descriptors: Graduate Students, Artificial Intelligence, Learner Engagement, Foreign Countries
Ming-Chi Tseng – Structural Equation Modeling: A Multidisciplinary Journal, 2025
This study aims to estimate the latent interaction effect in the CLPM model through a two-step multiple imputation analysis. The estimation of within x within and between x within latent interaction under the CLPM model framework is compared between the one-step Bayesian LMS method and the two-step multiple imputation analysis through a simulation…
Descriptors: Guidelines, Bayesian Statistics, Self Esteem, Depression (Psychology)
Caroline Bond; Vanessa Evans; Neil Humphrey – Journal of Research in Special Educational Needs, 2024
Schools are increasingly encouraged to adopt evidence-based or evidence informed interventions and implement them using insights from implementation science. The literature relating to implementation of interventions in schools has focused largely on universal interventions, particularly for social and emotional learning (SEL), which are designed…
Descriptors: Social Emotional Learning, Intervention, Program Implementation, Comparative Analysis
Xiaowen Liu – International Journal of Testing, 2024
Differential item functioning (DIF) often arises from multiple sources. Within the context of multidimensional item response theory, this study examined DIF items with varying secondary dimensions using the three DIF methods: SIBTEST, Mantel-Haenszel, and logistic regression. The effect of the number of secondary dimensions on DIF detection rates…
Descriptors: Item Analysis, Test Items, Item Response Theory, Correlation
Karl Schweizer; Andreas Gold; Dorothea Krampen; Stefan Troche – Educational and Psychological Measurement, 2024
Conceptualizing two-variable disturbances preventing good model fit in confirmatory factor analysis as item-level method effects instead of correlated residuals avoids violating the principle that residual variation is unique for each item. The possibility of representing such a disturbance by a method factor of a bifactor measurement model was…
Descriptors: Correlation, Factor Analysis, Measurement Techniques, Item Analysis
Judith Glaesser – International Journal of Social Research Methodology, 2024
Causal asymmetry is a situation where the causal factors under study are more suitable for explaining the outcome than its absence (or vice versa); they do not explain both equally well. In such a situation, presence of a cause leads to presence of the effect, but absence of the cause may not lead to absence of the effect. A conceptual discussion…
Descriptors: Comparative Analysis, Causal Models, Correlation, Foreign Countries