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Jingchen Liu; Gongjun Xu; Zhiliang Ying – Applied Psychological Measurement, 2012
The recent surge of interests in cognitive assessment has led to developments of novel statistical models for diagnostic classification. Central to many such models is the well-known "Q"-matrix, which specifies the item-attribute relationships. This article proposes a data-driven approach to identification of the "Q"-matrix and…
Descriptors: Matrices, Computation, Statistical Analysis, Models
Chen, Jinsong; de la Torre, Jimmy – Applied Psychological Measurement, 2013
Polytomous attributes, particularly those defined as part of the test development process, can provide additional diagnostic information. The present research proposes the polytomous generalized deterministic inputs, noisy, "and" gate (pG-DINA) model to accommodate such attributes. The pG-DINA model allows input from substantive experts…
Descriptors: Models, Cognitive Tests, Diagnostic Tests, Computation
Huebner, Alan; Li, Zhushan – Applied Psychological Measurement, 2012
Computerized classification tests (CCTs) classify examinees into categories such as pass/fail, master/nonmaster, and so on. This article proposes the use of stochastic methods from sequential analysis to address item overexposure, a practical concern in operational CCTs. Item overexposure is traditionally dealt with in CCTs by the Sympson-Hetter…
Descriptors: Computer Assisted Testing, Classification, Statistical Analysis, Test Items
Chiu, Chia-Yi – Applied Psychological Measurement, 2013
Most methods for fitting cognitive diagnosis models to educational test data and assigning examinees to proficiency classes require the Q-matrix that associates each item in a test with the cognitive skills (attributes) needed to answer it correctly. In most cases, the Q-matrix is not known but is constructed from the (fallible) judgments of…
Descriptors: Cognitive Tests, Diagnostic Tests, Models, Statistical Analysis
Babcock, Ben; Albano, Anthony D. – Applied Psychological Measurement, 2012
Testing programs often rely on common-item equating to maintain a single measurement scale across multiple test administrations and multiple years. Changes over time, in the item parameters and the latent trait underlying the scale, can lead to inaccurate score comparisons and misclassifications of examinees. This study examined how instability in…
Descriptors: Test Items, Measurement, Item Response Theory, Predictor Variables
DeCarlo, Lawrence T. – Applied Psychological Measurement, 2011
Cognitive diagnostic models (CDMs) attempt to uncover latent skills or attributes that examinees must possess in order to answer test items correctly. The DINA (deterministic input, noisy "and") model is a popular CDM that has been widely used. It is shown here that a logistic version of the model can easily be fit with standard software for…
Descriptors: Bayesian Statistics, Computation, Cognitive Tests, Diagnostic Tests
Finkelman, Matthew David – Applied Psychological Measurement, 2010
In sequential mastery testing (SMT), assessment via computer is used to classify examinees into one of two mutually exclusive categories. Unlike paper-and-pencil tests, SMT has the capability to use variable-length stopping rules. One approach to shortening variable-length tests is stochastic curtailment, which halts examination if the probability…
Descriptors: Mastery Tests, Computer Assisted Testing, Adaptive Testing, Test Length

Fleiss, Joseph L.; Cuzick, Jack – Applied Psychological Measurement, 1979
A reliability study is illustrated in which subjects are judged on a dichotomous trait by different sets of judges, possibly unequal in number. A kappa-like measure of reliability is proposed, its correspondence to an intraclass correlation coefficient is pointed out, and a test for its statistical significance is presented. (Author/CTM)
Descriptors: Classification, Correlation, Individual Characteristics, Informal Assessment

Mellenbergh, Gideon J.; van der Linden, Wim J. – Applied Psychological Measurement, 1979
For six tests, coefficient delta as an index for internal optimality is computed. Internal optimality is defined as the magnitude of risk of the decision procedure with respect to the true score. Results are compared with an alternative index (coefficient kappa) for assessing the consistency of decisions. (Author/JKS)
Descriptors: Classification, Comparative Analysis, Decision Making, Error of Measurement