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Showing 1 to 12 of 12 for “"Item Response Model"”.

  1. A Study of the Robustness of the Three-Parameter Item Response Model

    … to investigate the use of the three-parameter item response model on psychological test data which violated the model's assumptions of large sample sizes, long tests and test unidimensionality. The accuracy of the person ability and item characteristic curve parameter estimates derived by the …

    odu Repository record for A Study of the Robustness of the Three-Parameter Item Response Model (opens in a new tab)

  2. Dichotomous and polytomous item response model estimation using the marginal maximum likelihood and the EM algorithm

    Item Response Theory is a set oflatent variable techniques specifically designed to model the interaction between a respondent's latent trait/ability and the test items' characteristics such as difficulties, discrimination powers and guessing liabilities. The Item Response Theory framework …

    malta Repository record for Dichotomous and polytomous item response model estimation using the marginal maximum likelihood and the EM algorithm (opens in a new tab)

  3. A Comparison of Bayesian Estimation Techniques in a Multidimensional Two-Parameter Partial Credit Item Response Model

    … for parameter estimation in relatively simple item response models. However, extant literature is lacking on the investigation of Bayesian parameter estimation approaches for a multidimensional two parameter partial credit (M2PPC) model, therefore this simulation study investigated the …

    denver Repository record for A Comparison of Bayesian Estimation Techniques in a Multidimensional Two-Parameter Partial Credit Item Response Model (opens in a new tab)

  4. An investigation of the effects of test length on short-form basic skills competency tests developed by using the one-parameter item response model/

    … tests. developed by using the oneparameter item response model. Using the i tern responses of approximately 36,000 students to 75 items on a functional reading test, item parameters were estimated with the one-parameter i tern response model. Three nonoverlapping short-form tests of 10, 20, …

    vt Repository record for An investigation of the effects of test length on short-form basic skills competency tests developed by using the one-parameter item response model/ (opens in a new tab)

  5. Cluster Analysis for Cognitive Diagnosis: Theory and Applications

    Latent class models for cognitive diagnosis often begin with specification of a matrix that indicates which attributes or skills are needed for each item. Then by imposing restrictions that take this into account, along with a theory governing how subjects interact with items, parametric …

    uiuc Repository record for Cluster Analysis for Cognitive Diagnosis: Theory and Applications (opens in a new tab)

  6. A Bayesian Markov Chain Monte Carlo approach to the generalized graded unfolding model estimation: the future of non-cognitive measurement

    … Previous research has concluded that ideal point item response theory (IRT) models are more appropriate than dominance IRT models for measuring non-cognitive variables such as personality, vocational interests, attitudes, person-environment fit (e.g., person-job fit), etc. Although a couple of …

    uiuc Repository record for A Bayesian Markov Chain Monte Carlo approach to the generalized graded unfolding model estimation: the future of non-cognitive measurement (opens in a new tab)

  7. Latent trait estimation for item bundle structures

    Tests comprising item bundles, (i.e., groups of items related to common passages, paragraph, or graphs), have been treated as if they measure only a general trait, ignoring the within bundle dependencies. The consequences of not taking into account the specificity of each group of items are, in …

    uiuc Repository record for Latent trait estimation for item bundle structures (opens in a new tab)

  8. The Politics of Constitutional Review: Evidence from the European Court of Justice

    … of judges. I develop a general statistical model for aggregate data produced by subsets of deciders by extending the item-response model to account for selective participation in decisions. In addition, I explicitly model other known features of the parameters of the item-response model to …

    wustl Repository record for The Politics of Constitutional Review: Evidence from the European Court of Justice (opens in a new tab)

  9. Item parameter drift and online calibration

    An important assumption of item response theory based computerized adaptive assessment is item parameter invariance. Sometimes, however, item parameters are not invariant across different test administrations due to factors other than sampling error; and this phenomenon is termed item parameter …

    uiuc Repository record for Item parameter drift and online calibration (opens in a new tab)

  10. Calibration Efficacy of Three Logistic Models to the Degrees of Reading Power Test Using Residual Analysis

    … (DRP) calibrate their test using an item response model called the Rasch or one-parameter logistic model. The relationship between the use of the Rasch model in calibration of the DRP and the use of the DRP as a component of the Virginia Literacy Passport Testing Program (LPT) is …

    vt Repository record for Calibration Efficacy of Three Logistic Models to the Degrees of Reading Power Test Using Residual Analysis (opens in a new tab)

  11. Toward Culturally Responsive and Equitable Testing: Innovative Psychometric Analyses on Contextualized Measurement and Adaptive Testing

    … on cultural characteristics of contextualized items, students, and multigroup fairness from empirical and simulated datasets. The first study contributed to the understanding of culturally valid and equitable contextualized items, by implementing a coding rubric of item contexts followed by an …

    washington Repository record for Toward Culturally Responsive and Equitable Testing: Innovative Psychometric Analyses on Contextualized Measurement and Adaptive Testing (opens in a new tab)

  12. Integrative Biomarker Identification and Classification Using High Throughput Assays

    … to identify biomarkers predictive to therapy response or survival by integrating multiple assays including gene expression, methylation and copy number data through penalized regression. To identify key cancer-specific genes accounting for multiple mechanisms of regulation, we have developed …

    uthsc Repository record for Integrative Biomarker Identification and Classification Using High Throughput Assays (opens in a new tab)