Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 23 for “"Diagnostic Classification"”.
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Statistical Inference for Diagnostic Classification Models
Diagnostic classification models (DCM) are an important recent development in educational and psychological testing. Instead of an overall test score, a diagnostic test provides each subject with a profile detailing the concepts and skills (often called "attributes") that he/she has mastered. …
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Detection of Attribute Hierarchies and Classification Accuracy: the Value of the Hierarchical Diagnostic Classification Model in Formative Assessment Practices
… student is excelling or struggling in, cognitive diagnostic models are emerging as potentially effective and efficient tools. Despite the value of diagnostic models, there are concerns regarding the application of these models when as learning hierarchy is present or theorized; applying …
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A preliminary assessment of a framework for the allocation of comprehensive primary dental services
… DRAF comprises three inter-related components: a diagnostic classification tool, a timeframe for primary dental services, and dental team members of the Brazilian Family Health Programme. Aim: The aim of this study was to produce a preliminary assessment of the DRAF by determining its face …
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A preliminary assessment of a framework for the allocation of comprehensive primary dental services
… testing reliability and usability of its diagnostic classification tool, and to produce a set of preliminary recommendations on the viability of the DRAF before it is released for use within the Family Health Programme.
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Hippocampal Volume and the Detection of Mild Cognitive Impairment in an Older Adult Population: Assessing Performance on Cognitive Screeners Administered In-Person and Electronically
… sensitive to predicting group membership to the diagnostic classification of mild cognitive impairment compared to the Cogstate Brief Battery. The sample included 445 older adult participants selected from the Alzheimer’s Disease Neuroimaging Initiative 3. Participants met criteria for diagnostic …
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Identifying and Understanding Examinee Behaviors in Item Response Data that Compromise Psychometric Quality
… psychometric quality; we also validated a diagnostic classification model (DCM) aiming to diagnose the presence of misconceptions.
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Abbreviated and Expanded Forms of the Montreal Cognitive Assessment for Dementia Screening
… MCI and Alzheimer disease (AD) and compare the diagnostic classification accuracy of the SF-MoCA to the Mini-Mental State Examination (MMSE) and standard MoCA. Results revealed delayed recall, orientation, and serial subtraction items to be most useful in differentiating the diagnostic groups. …
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Industrial Scalable Rolling Element Bearing Diagnostic and Prognostic Modelling
… aircraft. The following thesis extends published diagnostic models for bearing condition through inline wear debris sensors through experimental observations and a physical understanding of the bearing degradation mechanics. This diagnostic classification model is scalable to bearings of other …
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An Investigation Of The Cognitive And Perceptual Mechanisms Involved In Mania-Proneness
… observed in Bipolar Disorder, implications for diagnostic classification, and the notion of Bipolar subtypes.
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Exertion therapy for the mentally subnormal child.
… children matched on age, sex and diagnostic classification, participated in the 30-week programme. Heart rate at rest, heart rate at sub minimal workload and maximal oxygen consumption rate estimates served as measures of physical fitness. Changes in intellectual and social …
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Does the Oswestry or SF-36 Help a Therapist to Predict Treatment Classification
… and a standardized physical examination and diagnostic classification system. The physical examination was performed by the evaluating therapists from the clinic and classification was determined by the evaluating therapists and the investigators to ensure correct subject placement into …
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Bridging the gap between clinicians' delivery and patients' experience of eating disorder diagnoses
… the controversies and challenges surrounding the diagnostic classification of eating disorders. However, research focusing on how patients experience their eating disorder diagnosis is scarce. The purpose of this research, therefore, was to address this gap in the literature by exploring patients’ …
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Autism Assessment from Home: Evaluating the Remote Childhood Autism Rating Scale, Second Edition (rCARS2) Observation for Tele-Assessment of Autism
… are a crucial component of face-to-face autism diagnostic evaluations, but few validated observation tools exist for remotely assessing autism across childhood, particularly for older children and adolescents, providing minimal guidance in this arena. Sanchez and Constantino (2020) previously …
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Trees and Forests: Data Science and Machine Learning Approaches to Characterise Clonal Haematopoiesis
… establishes data-driven refinements to diagnostic classification of clonal monocytoses, and sheds light on the selection pressures driving the emergence of high-risk splicing factor mutant clones.
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Predicting Language Impairment Status: A Risk Factor Model
… between the ages of 4;0 and 7;0 years. Two diagnostic classification schemes were used to examine the effects of clinical sample heterogeneity on risk factor model accuracy. In the first scheme, children were classified as SLI or TD based on their performance on a standardized expressive …
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Herbal medicines:physician's recommendation and clinical evaluation of St.John's Wort for depression
… trials suggested that use of different diagnostic classifications at the inclusion stage led to different estimates of effect. Similarly a significant difference in the estimates of efficacy was observed when trials were categorised according to length of follow-up. Confounding between …
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Novel Random Forest Methods and Algorithms for Autism Spectrum Disorders Research
… a proximity matrix for multivariate matching and diagnostic classification problems that are used for autism research (as an exemplary application). In observational studies, matching is used to optimize the balance between treatment groups. Although many matching algorithms can achieve this goal, …
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Cognitive diagnosis modeling and applications to assessing learning
… this chapter, we propose a mixture hidden Markov Diagnostic Classification Model framework for learning with response times and response accuracy. Such a model accounts for the heterogeneities in learning styles among students by modeling the different learning and response behaviors among …
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Machine Learning to Interrogate High-throughput Genomic Data: Theory and Applications
… mechanistic genes and achieving accurate diagnostic classification. Most existing multiclass gene selection methods heavily rely on the direct extension of two-class gene selection methods. However, simple extensions of binary discriminant analysis to multiclass gene selection are …
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Apathy and Impulsivity in Frontotemporal Lobar Degeneration Syndromes
… recent years, driving the development of novel diagnostic criteria. However, phenotypic boundaries are not always distinct and syndromes converge with disease progression, limiting the insights available from traditional diagnostic classification. Alternative transdiagnostic approaches may …
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