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Showing 1 to 15 of 17 results Save | Export
Haimiao Yuan – ProQuest LLC, 2022
The application of diagnostic classification models (DCMs) in the field of educational measurement is getting more attention in recent years. To make a valid inference from the model, it is important to ensure that the model fits the data. The purpose of the present study was to investigate the performance of the limited information…
Descriptors: Goodness of Fit, Educational Assessment, Educational Diagnosis, Models
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Nájera, Pablo; Sorrel, Miguel A.; Abad, Francisco José – Educational and Psychological Measurement, 2019
Cognitive diagnosis models (CDMs) are latent class multidimensional statistical models that help classify people accurately by using a set of discrete latent variables, commonly referred to as attributes. These models require a Q-matrix that indicates the attributes involved in each item. A potential problem is that the Q-matrix construction…
Descriptors: Matrices, Statistical Analysis, Models, Classification
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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
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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
von Davier, Matthias – Educational Testing Service, 2011
This report shows that the deterministic-input noisy-AND (DINA) model is a special case of more general compensatory diagnostic models by means of a reparameterization of the skill space and the design (Q-) matrix of item by skills associations. This reparameterization produces a compensatory model that is equivalent to the (conjunctive) DINA…
Descriptors: Clinical Diagnosis, Classification, Models, Matrices
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Martínez Abad, Fernando; Chaparro Caso López, Alicia A. – School Effectiveness and School Improvement, 2017
In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental,…
Descriptors: Foreign Countries, Data Collection, Statistical Analysis, Evaluation Methods
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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
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Rupp, Andre A.; Templin, Jonathan – Educational and Psychological Measurement, 2008
This article reports a study that investigated the effects of Q-matrix misspecifications on parameter estimates and misclassification rates for the deterministic-input, noisy "and" gate (DINA) model, which is a restricted latent class model for multiple classifications of respondents that can be useful for cognitively motivated diagnostic…
Descriptors: Program Effectiveness, Item Response Theory, Computation, Classification
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Levin, Joseph – Multivariate Behavioral Research, 1974
Descriptors: Classification, Correlation, Factor Analysis, Mathematical Models
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Peay, Edmund R. – Psychometrika, 1975
A class of closely related hierarchical grouping methods are discussed and a procedure which implements them in an integrated fashion is presented. These methods avoid some theoretical anomalies inherent in clustering and provide a framework for viewing partitioning and nonpartitioning grouping. Significant relationships between these methods and…
Descriptors: Classification, Cluster Grouping, Computer Programs, Data Analysis
WILLIAMS, J.H., JR. – 1967
CLASSIFICATION OF DOCUMENTS INVOLVES THREE DISTINCT PROCESSES-- (1) DEFINING A STRUCTURE OF CATEGORIES, (2) DETERMINING A BASIS FOR A CLASSIFICATION DECISION, AND (3) CLASSIFYING DOCUMENTS INTO CATEGORIES. OF THE THREE COMPUTER TECHNIQUES ARE DISCUSSED FOR THE LAST TWO. A WORD SELECTION MEASURE IS USED TO DELETE THOSE TERMS IN THE DOCUMENT THAT…
Descriptors: Classification, Correlation, Discriminant Analysis, Information Processing
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Davies, Roy – Journal of Documentation, 1985
Introduces Q-analysis, a methodology for investigating a wide range of structural phenomena that defines structures in terms of relations between members of sets and reveals their salient features by using techniques of algebraic topology. Applications relevant to librarianship and information science are reviewed and present limitations…
Descriptors: Change Agents, Classification, Equations (Mathematics), Graphs
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Huberty, Carl J.; Curry, Allen R. – 1975
A linear classification rule (used with equal covariance matrices) was contrasted with a quadratic rule (used with unequal covariance matrices) for accuracy of internal and external classification. The comparisons were made for seven situations which resulted from combining three data conditions (equal and unequal covariance matrices, minimal and…
Descriptors: Analysis of Covariance, Bayesian Statistics, Classification, Comparative Analysis
Statistical Reporting Service (USDA), Washington, DC. – 1974
Intended as a reference for the convenience of students in sampling, this monograph attempts to express relevant, introductory mathematics and probability in the context of sample surveys. Although some proofs are presented, the emphasis is more on exposition of mathematical language and concepts than on the mathematics per se and rigorous proofs.…
Descriptors: Agriculture, Algebra, Classification, Data Collection
Hooper, Frank H.; And Others – 1974
A series of Piagetian concrete operations period tasks dealing with classificatory concepts was administered to 280 children (40 subjects from each of seven levels--preschool, kindergarten, and first, second, third, fourth, and sixth grades). Significant main effects for age were found for all the tasks. Few significant sex differences were…
Descriptors: Children, Classification, Cognitive Ability, Concept Formation
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