NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 7 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Daoxuan Fu; Chunying Qin; Zhaosheng Luo; Yujun Li; Xiaofeng Yu; Ziyu Ye – Journal of Educational and Behavioral Statistics, 2025
One of the central components of cognitive diagnostic assessment is the Q-matrix, which is an essential loading indicator matrix and is typically constructed by subject matter experts. Nonetheless, to a large extent, the construction of Q-matrix remains a subjective process and might lead to misspecifications. Many researchers have recognized the…
Descriptors: Q Methodology, Matrices, Diagnostic Tests, Cognitive Measurement
Sales, Adam C.; Hansen, Ben B.; Rowan, Brian – Journal of Educational and Behavioral Statistics, 2018
In causal matching designs, some control subjects are often left unmatched, and some covariates are often left unmodeled. This article introduces "rebar," a method using high-dimensional modeling to incorporate these commonly discarded data without sacrificing the integrity of the matching design. After constructing a match, a researcher…
Descriptors: Computation, Prediction, Models, Data
Peer reviewed Peer reviewed
Direct linkDirect link
Stapleton, Laura M.; Yang, Ji Seung; Hancock, Gregory R. – Journal of Educational and Behavioral Statistics, 2016
We present types of constructs, individual- and cluster-level, and their confirmatory factor analytic validation models when data are from individuals nested within clusters. When a construct is theoretically individual level, spurious construct-irrelevant dependency in the data may appear to signal cluster-level dependency; in such cases,…
Descriptors: Multivariate Analysis, Factor Analysis, Validity, Models
Peer reviewed Peer reviewed
Direct linkDirect link
Koch, Tobias; Schultze, Martin; Burrus, Jeremy; Roberts, Richard D.; Eid, Michael – Journal of Educational and Behavioral Statistics, 2015
The numerous advantages of structural equation modeling (SEM) for the analysis of multitrait-multimethod (MTMM) data are well known. MTMM-SEMs allow researchers to explicitly model the measurement error, to examine the true convergent and discriminant validity of the given measures, and to relate external variables to the latent trait as well as…
Descriptors: Structural Equation Models, Hierarchical Linear Modeling, Factor Analysis, Multitrait Multimethod Techniques
Peer reviewed Peer reviewed
Bradlow, Eric T.; Thomas, Neal – Journal of Educational and Behavioral Statistics, 1998
A set of conditions is presented for the validity of inference for Item Response Theory (IRT) models applied to data collected from examinations that allow students to choose a subset of items. Common low-dimensional IRT models estimated by standard methods do not resolve the difficult problems posed by choice-based data. (SLD)
Descriptors: Inferences, Item Response Theory, Models, Selection
Peer reviewed Peer reviewed
Direct linkDirect link
Wiberg, Marie – Journal of Educational and Behavioral Statistics, 2003
A criterion-referenced computerized test is expressed as a statistical hypothesis problem. This admits that it can be studied by using the theory of optimal design. The power function of the statistical test is used as a criterion function when designing the test. A formal proof is provided showing that all items should have the same item…
Descriptors: Test Items, Computer Assisted Testing, Statistics, Validity
Peer reviewed Peer reviewed
Kaplan, David; Elliott, Pamela R. – Journal of Educational and Behavioral Statistics, 1997
Considers an approach to validating the selection of education indicators by incorporating them into a multilevel structural model and using the estimates from that model in policy-relevant simulations. The potential of this approach is demonstrated with data from the National Education Longitudinal Study of 1988. (SLD)
Descriptors: Educational Indicators, Educational Policy, Estimation (Mathematics), National Surveys