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Outcomes from a pilot dose comparison study of naming therapy in aphasia
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Responses to validating versus reframing support strategies as a function of borderline personality features and interpersonal problems
Agrammatic output in non-fluent, including Broca’s, aphasia as a rational behavior
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The Wechsler Adult Intelligence Scale-IV Cognitive Proficiency Index: alternate form reliability of the nine possible subtest tetrads
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Detecting Preknowledge Cheating via Innovative Measures: A Mixture Hierarchical Model for Jointly Modeling Item Responses, Response Times, and Visual Fixation Counts
Educational and Psychological Measurement, Volume 83, Issue 5, Page 1059-1080, October 2023.
Preknowledge cheating jeopardizes the validity of inferences based on test results. Many methods have been developed to detect preknowledge cheating by jointly analyzing item responses and response times. Gaze fixations, an essential eye-tracker measure, can be utilized to help detect aberrant testing behavior with improved accuracy beyond using product and process data types in isolation. As such, this study proposes a mixture hierarchical model that integrates item responses, response times, and visual fixation counts collected from an eye-tracker (a) to detect aberrant test takers who have different levels of preknowledge and (b) to account for nuances in behavioral patterns between normally-behaved and aberrant examinees. A Bayesian approach to estimating model parameters is carried out via an MCMC algorithm. Finally, the proposed model is applied to experimental data to illustrate how the model can be used to identify test takers having preknowledge on the test items.
Preknowledge cheating jeopardizes the validity of inferences based on test results. Many methods have been developed to detect preknowledge cheating by jointly analyzing item responses and response times. Gaze fixations, an essential eye-tracker measure, can be utilized to help detect aberrant testing behavior with improved accuracy beyond using product and process data types in isolation. As such, this study proposes a mixture hierarchical model that integrates item responses, response times, and visual fixation counts collected from an eye-tracker (a) to detect aberrant test takers who have different levels of preknowledge and (b) to account for nuances in behavioral patterns between normally-behaved and aberrant examinees. A Bayesian approach to estimating model parameters is carried out via an MCMC algorithm. Finally, the proposed model is applied to experimental data to illustrate how the model can be used to identify test takers having preknowledge on the test items.
Classification of performance validity and symptom validity using the Trauma Symptom Inventory-2
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White matter microstructure and executive functions in congenital heart disease from childhood to adulthood: A pooled case–control study
Verb Frequency and Density Drive Naming Performance in Primary Progressive Aphasia
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