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You searched for subject:(diagnostic classification model). Showing records 1 – 13 of 13 total matches.

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University of Georgia

1. Bradshaw, Laine Percell. Combining scaling and classification: A psychometric model for scaling ability and diagnosing misconceptions.

Degree: PhD, Educational Psychology, 2011, University of Georgia

 The Scaling Individuals and Classifying Misconceptions (SICM) model is presented as a combination of an item response theory (IRT) model and a diagnostic classification model(more)

Subjects/Keywords: diagnostic classification model

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APA (6th Edition):

Bradshaw, L. P. (2011). Combining scaling and classification: A psychometric model for scaling ability and diagnosing misconceptions. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/bradshaw_laine_p_201105_phd

Chicago Manual of Style (16th Edition):

Bradshaw, Laine Percell. “Combining scaling and classification: A psychometric model for scaling ability and diagnosing misconceptions.” 2011. Doctoral Dissertation, University of Georgia. Accessed July 17, 2019. http://purl.galileo.usg.edu/uga_etd/bradshaw_laine_p_201105_phd.

MLA Handbook (7th Edition):

Bradshaw, Laine Percell. “Combining scaling and classification: A psychometric model for scaling ability and diagnosing misconceptions.” 2011. Web. 17 Jul 2019.

Vancouver:

Bradshaw LP. Combining scaling and classification: A psychometric model for scaling ability and diagnosing misconceptions. [Internet] [Doctoral dissertation]. University of Georgia; 2011. [cited 2019 Jul 17]. Available from: http://purl.galileo.usg.edu/uga_etd/bradshaw_laine_p_201105_phd.

Council of Science Editors:

Bradshaw LP. Combining scaling and classification: A psychometric model for scaling ability and diagnosing misconceptions. [Doctoral Dissertation]. University of Georgia; 2011. Available from: http://purl.galileo.usg.edu/uga_etd/bradshaw_laine_p_201105_phd


University of Kansas

2. Pan, Qianqian. Growth Modeling in a Diagnostic Classification Model (DCM) Framework.

Degree: PhD, Psychology & Research in Education, 2018, University of Kansas

 A multivariate longitudinal DCM is developed that is the composite of two components, the log-linear cognitive diagnostic model (LCDM) as the measurement model component that… (more)

Subjects/Keywords: Educational tests & measurements; Diagnostic Classification Model; Growth Curve Model; Longitudinal Data

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APA (6th Edition):

Pan, Q. (2018). Growth Modeling in a Diagnostic Classification Model (DCM) Framework. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/28027

Chicago Manual of Style (16th Edition):

Pan, Qianqian. “Growth Modeling in a Diagnostic Classification Model (DCM) Framework.” 2018. Doctoral Dissertation, University of Kansas. Accessed July 17, 2019. http://hdl.handle.net/1808/28027.

MLA Handbook (7th Edition):

Pan, Qianqian. “Growth Modeling in a Diagnostic Classification Model (DCM) Framework.” 2018. Web. 17 Jul 2019.

Vancouver:

Pan Q. Growth Modeling in a Diagnostic Classification Model (DCM) Framework. [Internet] [Doctoral dissertation]. University of Kansas; 2018. [cited 2019 Jul 17]. Available from: http://hdl.handle.net/1808/28027.

Council of Science Editors:

Pan Q. Growth Modeling in a Diagnostic Classification Model (DCM) Framework. [Doctoral Dissertation]. University of Kansas; 2018. Available from: http://hdl.handle.net/1808/28027


University of South Carolina

3. FENG, YULING. Estimation and Q-matrix validation for diagnostic classification models.

Degree: PhD, Statistics, 2013, University of South Carolina

Diagnostic classification models (DCMs) are structured latent class models widely discussed in the field of psychometrics. They model subjects' underlying attribute patterns and classify… (more)

Subjects/Keywords: Physical Sciences and Mathematics; Statistics and Probability; diagnostic classification models; model estimation; Q-matrix validation

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APA (6th Edition):

FENG, Y. (2013). Estimation and Q-matrix validation for diagnostic classification models. (Doctoral Dissertation). University of South Carolina. Retrieved from https://scholarcommons.sc.edu/etd/2611

Chicago Manual of Style (16th Edition):

FENG, YULING. “Estimation and Q-matrix validation for diagnostic classification models.” 2013. Doctoral Dissertation, University of South Carolina. Accessed July 17, 2019. https://scholarcommons.sc.edu/etd/2611.

MLA Handbook (7th Edition):

FENG, YULING. “Estimation and Q-matrix validation for diagnostic classification models.” 2013. Web. 17 Jul 2019.

Vancouver:

FENG Y. Estimation and Q-matrix validation for diagnostic classification models. [Internet] [Doctoral dissertation]. University of South Carolina; 2013. [cited 2019 Jul 17]. Available from: https://scholarcommons.sc.edu/etd/2611.

Council of Science Editors:

FENG Y. Estimation and Q-matrix validation for diagnostic classification models. [Doctoral Dissertation]. University of South Carolina; 2013. Available from: https://scholarcommons.sc.edu/etd/2611


University of Kansas

4. Thompson, William. Evaluating Model Estimation Processes for Diagnostic Classification Models.

Degree: PhD, Psychology & Research in Education, 2018, University of Kansas

Diagnostic classification models (DCMs) are a class of models that define respondent ability on a set of predefined categorical latent variables. In recent years, the… (more)

Subjects/Keywords: Educational tests & measurements; Educational psychology; Quantitative psychology; diagnostic classification models; log-linear cognitive diagnosis model; model reduction; Monte Carlo simulation

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APA (6th Edition):

Thompson, W. (2018). Evaluating Model Estimation Processes for Diagnostic Classification Models. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/27568

Chicago Manual of Style (16th Edition):

Thompson, William. “Evaluating Model Estimation Processes for Diagnostic Classification Models.” 2018. Doctoral Dissertation, University of Kansas. Accessed July 17, 2019. http://hdl.handle.net/1808/27568.

MLA Handbook (7th Edition):

Thompson, William. “Evaluating Model Estimation Processes for Diagnostic Classification Models.” 2018. Web. 17 Jul 2019.

Vancouver:

Thompson W. Evaluating Model Estimation Processes for Diagnostic Classification Models. [Internet] [Doctoral dissertation]. University of Kansas; 2018. [cited 2019 Jul 17]. Available from: http://hdl.handle.net/1808/27568.

Council of Science Editors:

Thompson W. Evaluating Model Estimation Processes for Diagnostic Classification Models. [Doctoral Dissertation]. University of Kansas; 2018. Available from: http://hdl.handle.net/1808/27568


University of Georgia

5. Zor, Selay. Designing field tests for multidimensional classification models.

Degree: MA, Educational Psychology, 2018, University of Georgia

Diagnostic classification models (DCMs) are multidimensional latent variable models that can provide diagnostic information about the mastery state of examinees’ knowledge components (Rupp, Templin &… (more)

Subjects/Keywords: Diagnostic classification models; Log-linear cognitive diagnosis model; field-testing; item tryouts; planned missing data design

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APA (6th Edition):

Zor, S. (2018). Designing field tests for multidimensional classification models. (Masters Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/38528

Chicago Manual of Style (16th Edition):

Zor, Selay. “Designing field tests for multidimensional classification models.” 2018. Masters Thesis, University of Georgia. Accessed July 17, 2019. http://hdl.handle.net/10724/38528.

MLA Handbook (7th Edition):

Zor, Selay. “Designing field tests for multidimensional classification models.” 2018. Web. 17 Jul 2019.

Vancouver:

Zor S. Designing field tests for multidimensional classification models. [Internet] [Masters thesis]. University of Georgia; 2018. [cited 2019 Jul 17]. Available from: http://hdl.handle.net/10724/38528.

Council of Science Editors:

Zor S. Designing field tests for multidimensional classification models. [Masters Thesis]. University of Georgia; 2018. Available from: http://hdl.handle.net/10724/38528

6. El Assaad, Hani. Modélisation et classification dynamique de données temporelles non stationnaires : Dynamic classification and modeling of non-stationary temporal data.

Degree: Docteur es, Signal, Image, Automatique, 2014, Université Paris-Est

Cette thèse aborde la problématique de la classification non supervisée de données lorsque les caractéristiques des classes sont susceptibles d'évoluer au cours du temps. On… (more)

Subjects/Keywords: Diagnostic; Classification automatique; Modèle de mélange; Données temporelles non stationnaires; Classes évolutives; Filtre de Kalman; Diagnosis; Clustering; Dynamic latent variable model; Temporal data clustering; Evolving clusters; Kalman filter

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APA (6th Edition):

El Assaad, H. (2014). Modélisation et classification dynamique de données temporelles non stationnaires : Dynamic classification and modeling of non-stationary temporal data. (Doctoral Dissertation). Université Paris-Est. Retrieved from http://www.theses.fr/2014PEST1162

Chicago Manual of Style (16th Edition):

El Assaad, Hani. “Modélisation et classification dynamique de données temporelles non stationnaires : Dynamic classification and modeling of non-stationary temporal data.” 2014. Doctoral Dissertation, Université Paris-Est. Accessed July 17, 2019. http://www.theses.fr/2014PEST1162.

MLA Handbook (7th Edition):

El Assaad, Hani. “Modélisation et classification dynamique de données temporelles non stationnaires : Dynamic classification and modeling of non-stationary temporal data.” 2014. Web. 17 Jul 2019.

Vancouver:

El Assaad H. Modélisation et classification dynamique de données temporelles non stationnaires : Dynamic classification and modeling of non-stationary temporal data. [Internet] [Doctoral dissertation]. Université Paris-Est; 2014. [cited 2019 Jul 17]. Available from: http://www.theses.fr/2014PEST1162.

Council of Science Editors:

El Assaad H. Modélisation et classification dynamique de données temporelles non stationnaires : Dynamic classification and modeling of non-stationary temporal data. [Doctoral Dissertation]. Université Paris-Est; 2014. Available from: http://www.theses.fr/2014PEST1162


University of Melbourne

7. SOON, SIEW PENG. Anorexia nervosa: controversy regarding diagnostic criteria and evidence for control-related cognitive and metacognitive mechanisms maintaining the disorder.

Degree: 2012, University of Melbourne

 Background: The study was divided into three sections. (i) The utility of current controversial physical diagnostic criteria for Anorexia Nervosa (AN), specifically, the weight threshold… (more)

Subjects/Keywords: eating disorder; anorexia nervosa; diagnostic criteria; classification; subthreshold; DSM; weight; amenorrhea; perfectionism; self-esteem; control; metacognition; dietary restraint; drive for thinness; cognitive model; cognitive therapy; metacognitive therapy

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APA (6th Edition):

SOON, S. P. (2012). Anorexia nervosa: controversy regarding diagnostic criteria and evidence for control-related cognitive and metacognitive mechanisms maintaining the disorder. (Doctoral Dissertation). University of Melbourne. Retrieved from http://hdl.handle.net/11343/38124

Chicago Manual of Style (16th Edition):

SOON, SIEW PENG. “Anorexia nervosa: controversy regarding diagnostic criteria and evidence for control-related cognitive and metacognitive mechanisms maintaining the disorder.” 2012. Doctoral Dissertation, University of Melbourne. Accessed July 17, 2019. http://hdl.handle.net/11343/38124.

MLA Handbook (7th Edition):

SOON, SIEW PENG. “Anorexia nervosa: controversy regarding diagnostic criteria and evidence for control-related cognitive and metacognitive mechanisms maintaining the disorder.” 2012. Web. 17 Jul 2019.

Vancouver:

SOON SP. Anorexia nervosa: controversy regarding diagnostic criteria and evidence for control-related cognitive and metacognitive mechanisms maintaining the disorder. [Internet] [Doctoral dissertation]. University of Melbourne; 2012. [cited 2019 Jul 17]. Available from: http://hdl.handle.net/11343/38124.

Council of Science Editors:

SOON SP. Anorexia nervosa: controversy regarding diagnostic criteria and evidence for control-related cognitive and metacognitive mechanisms maintaining the disorder. [Doctoral Dissertation]. University of Melbourne; 2012. Available from: http://hdl.handle.net/11343/38124


Université de Montréal

8. Duong Thi, Dan Thanh. Modélisation, élaboration et évaluation de rapports à visée diagnostique des données du PIRLS 2011 .

Degree: 2019, Université de Montréal

Subjects/Keywords: approche diagnostique cognitive; modèle de classification diagnostique; DINA; G-DINA; lecture; PIRLS 2011; élaboration des rapports diagnostiques; évaluation des rapports diagnostiques; Cognitive diagnostic approach; Diagnostic classification model; Reading; Diagnostic report development; Diagnostic report evaluation

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APA (6th Edition):

Duong Thi, D. T. (2019). Modélisation, élaboration et évaluation de rapports à visée diagnostique des données du PIRLS 2011 . (Thesis). Université de Montréal. Retrieved from http://hdl.handle.net/1866/21829

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Duong Thi, Dan Thanh. “Modélisation, élaboration et évaluation de rapports à visée diagnostique des données du PIRLS 2011 .” 2019. Thesis, Université de Montréal. Accessed July 17, 2019. http://hdl.handle.net/1866/21829.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Duong Thi, Dan Thanh. “Modélisation, élaboration et évaluation de rapports à visée diagnostique des données du PIRLS 2011 .” 2019. Web. 17 Jul 2019.

Vancouver:

Duong Thi DT. Modélisation, élaboration et évaluation de rapports à visée diagnostique des données du PIRLS 2011 . [Internet] [Thesis]. Université de Montréal; 2019. [cited 2019 Jul 17]. Available from: http://hdl.handle.net/1866/21829.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Duong Thi DT. Modélisation, élaboration et évaluation de rapports à visée diagnostique des données du PIRLS 2011 . [Thesis]. Université de Montréal; 2019. Available from: http://hdl.handle.net/1866/21829

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

9. Alagoz Ekici, Cigdem. Posterior predictive model checking for the diagnostic input noisy and gate model.

Degree: PhD, Educational Psychology, 2012, University of Georgia

 This study presents a posterior predictive model checking (PPMC) method for the deterministic inputs, noisy and gate (DINA) model. The potential of the PPMC method… (more)

Subjects/Keywords: PPMC; Bayesian model fit; Model evaluation; Diagnostic classification; Higher order DINA model

…Introduction A number of diagnostic classification models (DCMs) have been proposed… …multidimensional latent variables. One family of these models are known as diagnostic classification… …given α in the context of diagnostic classification models. For a response pattern y, the… …model provides diagnostic feedback from a measurement. The objective of higher-order latent… …DINA model, to provide more specific cognitive diagnostic information in the test results. In… 

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APA (6th Edition):

Alagoz Ekici, C. (2012). Posterior predictive model checking for the diagnostic input noisy and gate model. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/alagoz-ekici_cigdem_201208_phd

Chicago Manual of Style (16th Edition):

Alagoz Ekici, Cigdem. “Posterior predictive model checking for the diagnostic input noisy and gate model.” 2012. Doctoral Dissertation, University of Georgia. Accessed July 17, 2019. http://purl.galileo.usg.edu/uga_etd/alagoz-ekici_cigdem_201208_phd.

MLA Handbook (7th Edition):

Alagoz Ekici, Cigdem. “Posterior predictive model checking for the diagnostic input noisy and gate model.” 2012. Web. 17 Jul 2019.

Vancouver:

Alagoz Ekici C. Posterior predictive model checking for the diagnostic input noisy and gate model. [Internet] [Doctoral dissertation]. University of Georgia; 2012. [cited 2019 Jul 17]. Available from: http://purl.galileo.usg.edu/uga_etd/alagoz-ekici_cigdem_201208_phd.

Council of Science Editors:

Alagoz Ekici C. Posterior predictive model checking for the diagnostic input noisy and gate model. [Doctoral Dissertation]. University of Georgia; 2012. Available from: http://purl.galileo.usg.edu/uga_etd/alagoz-ekici_cigdem_201208_phd


Université de Grenoble

10. Hamaz, Tahar. Outils de caractérisation et de diagnostic d'une pile à combustible de type PEM par mesure du champ électromagnétique externe : Diagnosis of a PEM fuel cell by measurement of the external electromagnetic field.

Degree: Docteur es, Automatique et productique, 2014, Université de Grenoble

 Les piles à combustible à membrane échangeuse de protons (PEMFC) constituent une alternative aux moteurs thermiques utilisés dans le cadre d’applications transport ou dans le… (more)

Subjects/Keywords: Pile à combustible de type PEM; Modèle de représentation; Diagnostic; Classification; Distribution de la densité de courant; Champ magnétique; PEM fuel cell; Representation model; Diagnosis; Classification; Current density distribution; Magnetic field; 620

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APA (6th Edition):

Hamaz, T. (2014). Outils de caractérisation et de diagnostic d'une pile à combustible de type PEM par mesure du champ électromagnétique externe : Diagnosis of a PEM fuel cell by measurement of the external electromagnetic field. (Doctoral Dissertation). Université de Grenoble. Retrieved from http://www.theses.fr/2014GRENT074

Chicago Manual of Style (16th Edition):

Hamaz, Tahar. “Outils de caractérisation et de diagnostic d'une pile à combustible de type PEM par mesure du champ électromagnétique externe : Diagnosis of a PEM fuel cell by measurement of the external electromagnetic field.” 2014. Doctoral Dissertation, Université de Grenoble. Accessed July 17, 2019. http://www.theses.fr/2014GRENT074.

MLA Handbook (7th Edition):

Hamaz, Tahar. “Outils de caractérisation et de diagnostic d'une pile à combustible de type PEM par mesure du champ électromagnétique externe : Diagnosis of a PEM fuel cell by measurement of the external electromagnetic field.” 2014. Web. 17 Jul 2019.

Vancouver:

Hamaz T. Outils de caractérisation et de diagnostic d'une pile à combustible de type PEM par mesure du champ électromagnétique externe : Diagnosis of a PEM fuel cell by measurement of the external electromagnetic field. [Internet] [Doctoral dissertation]. Université de Grenoble; 2014. [cited 2019 Jul 17]. Available from: http://www.theses.fr/2014GRENT074.

Council of Science Editors:

Hamaz T. Outils de caractérisation et de diagnostic d'une pile à combustible de type PEM par mesure du champ électromagnétique externe : Diagnosis of a PEM fuel cell by measurement of the external electromagnetic field. [Doctoral Dissertation]. Université de Grenoble; 2014. Available from: http://www.theses.fr/2014GRENT074

11. Li, Zhongliang. Data-driven fault diagnosis for PEMFC systems : Integrating representation and classification methods for obstacle detection in road scenes.

Degree: Docteur es, Automatique, 2014, Aix Marseille Université

Cette thèse est consacrée à l'étude de diagnostic de pannes pour les systèmes pile à combustible de type PEMFC. Le but est d'améliorer la fiabilité… (more)

Subjects/Keywords: Système PEMFC; Diagnostic en ligne; Des tensions cellulaires; Reconnaissance de forme; La précision du diagnostic; Le coût de calcul; Systèmes embarqués; La détection des défauts roman; Adaptation en ligne; L'identification du modèle; PEMFC system; Online diagnosis; Cell voltages; Pattern classification; Diagnosis accuracy; Computational cost; Embedded system; Novel fault detection; Online adaptation; Model identification

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APA (6th Edition):

Li, Z. (2014). Data-driven fault diagnosis for PEMFC systems : Integrating representation and classification methods for obstacle detection in road scenes. (Doctoral Dissertation). Aix Marseille Université. Retrieved from http://www.theses.fr/2014AIXM4335

Chicago Manual of Style (16th Edition):

Li, Zhongliang. “Data-driven fault diagnosis for PEMFC systems : Integrating representation and classification methods for obstacle detection in road scenes.” 2014. Doctoral Dissertation, Aix Marseille Université. Accessed July 17, 2019. http://www.theses.fr/2014AIXM4335.

MLA Handbook (7th Edition):

Li, Zhongliang. “Data-driven fault diagnosis for PEMFC systems : Integrating representation and classification methods for obstacle detection in road scenes.” 2014. Web. 17 Jul 2019.

Vancouver:

Li Z. Data-driven fault diagnosis for PEMFC systems : Integrating representation and classification methods for obstacle detection in road scenes. [Internet] [Doctoral dissertation]. Aix Marseille Université 2014. [cited 2019 Jul 17]. Available from: http://www.theses.fr/2014AIXM4335.

Council of Science Editors:

Li Z. Data-driven fault diagnosis for PEMFC systems : Integrating representation and classification methods for obstacle detection in road scenes. [Doctoral Dissertation]. Aix Marseille Université 2014. Available from: http://www.theses.fr/2014AIXM4335

12. Lao, Hongling. Estimation of Diagnostic Classification Models without Constraints: Issues with Class Label Switching.

Degree: M.S.Ed., Psychology & Research in Education, 2016, University of Kansas

Diagnostic classification models (DCMs) may suffer from the latent class label switching issue. Label switching refers to the situation where the labels for the parameters… (more)

Subjects/Keywords: Educational psychology; Quantitative psychology; Statistics; diagnostic classification models; estimation; label switching; latent class analysis; local optimal solution; model constraints

…linear cognitive diagnostic measurement model. For each unique dataset, Mplus 7.3 (Muthen… …for the person classification parameters. For the model without constraints, both the high… …measurement model, and the person latent class classification respectively. The bias and the root… …individual parameter for the measurement model. For the person classification accuracy, the… …classification accuracy was slightly higher for the model with constraints condition than the model… 

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APA (6th Edition):

Lao, H. (2016). Estimation of Diagnostic Classification Models without Constraints: Issues with Class Label Switching. (Masters Thesis). University of Kansas. Retrieved from http://hdl.handle.net/1808/23928

Chicago Manual of Style (16th Edition):

Lao, Hongling. “Estimation of Diagnostic Classification Models without Constraints: Issues with Class Label Switching.” 2016. Masters Thesis, University of Kansas. Accessed July 17, 2019. http://hdl.handle.net/1808/23928.

MLA Handbook (7th Edition):

Lao, Hongling. “Estimation of Diagnostic Classification Models without Constraints: Issues with Class Label Switching.” 2016. Web. 17 Jul 2019.

Vancouver:

Lao H. Estimation of Diagnostic Classification Models without Constraints: Issues with Class Label Switching. [Internet] [Masters thesis]. University of Kansas; 2016. [cited 2019 Jul 17]. Available from: http://hdl.handle.net/1808/23928.

Council of Science Editors:

Lao H. Estimation of Diagnostic Classification Models without Constraints: Issues with Class Label Switching. [Masters Thesis]. University of Kansas; 2016. Available from: http://hdl.handle.net/1808/23928

13. Hamilton, Erin Kinzel. Multiscale and meta-analytic approaches to inference in clinical healthcare data.

Degree: PhD, Biomedical Engineering, 2013, Georgia Tech

 The field of medicine is regularly faced with the challenge of utilizing information that is complicated or difficult to characterize. Physicians often must use their… (more)

Subjects/Keywords: Rasch model; Bayesian hierarchical model; Paired data; Meta-analysis; Heterogeneity; Scale-mixing wavelet transform; Sampling distribution; Bootstrapping; Dental sealants; Waveletes; Spectral tools; Breast cancer; Scaling; Wavelet spectra; Weighted regression; Theil; Microcalcification; Diagnostic classification; Image enhancement; Rasch models; Item response theory; Sampling (Statistics); Bootstrap (Statistics)

…44 18 Results of classification by logistic regression using Hd . . . . . . . . . . 48… …19 Results of classification by logistic regression using (Hd , Hh )… …49 20 Results of classification by logistic regression using (Hd , Hv , Hh )… …50 21 Results of linear and quadratic classification based on pair (Hd , Hh )… …Binary Classification Outcomes . . . . . . . . . . . . . . . . . . . . . . . 86 17 ix LIST… 

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APA (6th Edition):

Hamilton, E. K. (2013). Multiscale and meta-analytic approaches to inference in clinical healthcare data. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/47600

Chicago Manual of Style (16th Edition):

Hamilton, Erin Kinzel. “Multiscale and meta-analytic approaches to inference in clinical healthcare data.” 2013. Doctoral Dissertation, Georgia Tech. Accessed July 17, 2019. http://hdl.handle.net/1853/47600.

MLA Handbook (7th Edition):

Hamilton, Erin Kinzel. “Multiscale and meta-analytic approaches to inference in clinical healthcare data.” 2013. Web. 17 Jul 2019.

Vancouver:

Hamilton EK. Multiscale and meta-analytic approaches to inference in clinical healthcare data. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Jul 17]. Available from: http://hdl.handle.net/1853/47600.

Council of Science Editors:

Hamilton EK. Multiscale and meta-analytic approaches to inference in clinical healthcare data. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/47600

.