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- 2006 – 2010 (12)

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Hong Kong University of Science and Technology

1.
Poon, Kin Man.
* Latent* tree models : an application and an extension.

Degree: 2012, Hong Kong University of Science and Technology

URL: http://repository.ust.hk/ir/Record/1783.1-7736 ; https://doi.org/10.14711/thesis-b1198634 ; http://repository.ust.hk/ir/bitstream/1783.1-7736/1/th_redirect.html

► *Latent* tree models are a class of probabilistic graphical models. These models have a tree structure, in which the internal nodes represent *latent* *variables* whereas…
(more)

Subjects/Keywords: Latent structure analysis ; Latent variables

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Poon, K. M. (2012). Latent tree models : an application and an extension. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-7736 ; https://doi.org/10.14711/thesis-b1198634 ; http://repository.ust.hk/ir/bitstream/1783.1-7736/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Poon, Kin Man. “Latent tree models : an application and an extension.” 2012. Thesis, Hong Kong University of Science and Technology. Accessed October 25, 2020. http://repository.ust.hk/ir/Record/1783.1-7736 ; https://doi.org/10.14711/thesis-b1198634 ; http://repository.ust.hk/ir/bitstream/1783.1-7736/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Poon, Kin Man. “Latent tree models : an application and an extension.” 2012. Web. 25 Oct 2020.

Vancouver:

Poon KM. Latent tree models : an application and an extension. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2012. [cited 2020 Oct 25]. Available from: http://repository.ust.hk/ir/Record/1783.1-7736 ; https://doi.org/10.14711/thesis-b1198634 ; http://repository.ust.hk/ir/bitstream/1783.1-7736/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Poon KM. Latent tree models : an application and an extension. [Thesis]. Hong Kong University of Science and Technology; 2012. Available from: http://repository.ust.hk/ir/Record/1783.1-7736 ; https://doi.org/10.14711/thesis-b1198634 ; http://repository.ust.hk/ir/bitstream/1783.1-7736/1/th_redirect.html

Not specified: Masters Thesis or Doctoral Dissertation

2. Iaconangelo, Charles Joseph, 1985-. Uses of classification error probabilities in the three-step approach to estimating cognitive diagnosis models.

Degree: PhD, Education, 2017, Rutgers University

URL: https://rucore.libraries.rutgers.edu/rutgers-lib/55495/

►

Classification error probabilities (CEPs) are estimates of the amount of misclassification in the measurement model conditional on the true *latent* class memberships. CEPs can be…
(more)

Subjects/Keywords: Latent variables; Latent structure analysis

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APA (6^{th} Edition):

Iaconangelo, Charles Joseph, 1. (2017). Uses of classification error probabilities in the three-step approach to estimating cognitive diagnosis models. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/55495/

Chicago Manual of Style (16^{th} Edition):

Iaconangelo, Charles Joseph, 1985-. “Uses of classification error probabilities in the three-step approach to estimating cognitive diagnosis models.” 2017. Doctoral Dissertation, Rutgers University. Accessed October 25, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/55495/.

MLA Handbook (7^{th} Edition):

Iaconangelo, Charles Joseph, 1985-. “Uses of classification error probabilities in the three-step approach to estimating cognitive diagnosis models.” 2017. Web. 25 Oct 2020.

Vancouver:

Iaconangelo, Charles Joseph 1. Uses of classification error probabilities in the three-step approach to estimating cognitive diagnosis models. [Internet] [Doctoral dissertation]. Rutgers University; 2017. [cited 2020 Oct 25]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/55495/.

Council of Science Editors:

Iaconangelo, Charles Joseph 1. Uses of classification error probabilities in the three-step approach to estimating cognitive diagnosis models. [Doctoral Dissertation]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/55495/

Hong Kong University of Science and Technology

3.
Liu, Tengfei.
Accelerated learning of *latent* tree models for topic detection and multidimensional clustering.

Degree: 2015, Hong Kong University of Science and Technology

URL: http://repository.ust.hk/ir/Record/1783.1-74522 ; https://doi.org/10.14711/thesis-b1477729 ; http://repository.ust.hk/ir/bitstream/1783.1-74522/1/th_redirect.html

► *Latent* tree models (LTMs) are tree-structured probabilistic graphical models where the *variables* at leaf nodes are observed and the *variables* at internal nodes are *latent*.…
(more)

Subjects/Keywords: Latent structure analysis ; Latent variables ; Multivariate analysis

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APA (6^{th} Edition):

Liu, T. (2015). Accelerated learning of latent tree models for topic detection and multidimensional clustering. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-74522 ; https://doi.org/10.14711/thesis-b1477729 ; http://repository.ust.hk/ir/bitstream/1783.1-74522/1/th_redirect.html

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Liu, Tengfei. “Accelerated learning of latent tree models for topic detection and multidimensional clustering.” 2015. Thesis, Hong Kong University of Science and Technology. Accessed October 25, 2020. http://repository.ust.hk/ir/Record/1783.1-74522 ; https://doi.org/10.14711/thesis-b1477729 ; http://repository.ust.hk/ir/bitstream/1783.1-74522/1/th_redirect.html.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Liu, Tengfei. “Accelerated learning of latent tree models for topic detection and multidimensional clustering.” 2015. Web. 25 Oct 2020.

Vancouver:

Liu T. Accelerated learning of latent tree models for topic detection and multidimensional clustering. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2015. [cited 2020 Oct 25]. Available from: http://repository.ust.hk/ir/Record/1783.1-74522 ; https://doi.org/10.14711/thesis-b1477729 ; http://repository.ust.hk/ir/bitstream/1783.1-74522/1/th_redirect.html.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Liu T. Accelerated learning of latent tree models for topic detection and multidimensional clustering. [Thesis]. Hong Kong University of Science and Technology; 2015. Available from: http://repository.ust.hk/ir/Record/1783.1-74522 ; https://doi.org/10.14711/thesis-b1477729 ; http://repository.ust.hk/ir/bitstream/1783.1-74522/1/th_redirect.html

Not specified: Masters Thesis or Doctoral Dissertation

Columbia University

4.
Mittel, Louis Buchalter.
Efficient Estimation of the Expectation of a *Latent* Variable in the Presence of *Subject*-Specific Ancillaries.

Degree: 2017, Columbia University

URL: https://doi.org/10.7916/D8JW8SFB

► *Latent* *variables* are often included in a model in order to capture the diversity among subjects in a population. Sometimes the distribution of these *latent*…
(more)

Subjects/Keywords: Statistics; Latent variables; Estimation theory

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APA (6^{th} Edition):

Mittel, L. B. (2017). Efficient Estimation of the Expectation of a Latent Variable in the Presence of Subject-Specific Ancillaries. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8JW8SFB

Chicago Manual of Style (16^{th} Edition):

Mittel, Louis Buchalter. “Efficient Estimation of the Expectation of a Latent Variable in the Presence of Subject-Specific Ancillaries.” 2017. Doctoral Dissertation, Columbia University. Accessed October 25, 2020. https://doi.org/10.7916/D8JW8SFB.

MLA Handbook (7^{th} Edition):

Mittel, Louis Buchalter. “Efficient Estimation of the Expectation of a Latent Variable in the Presence of Subject-Specific Ancillaries.” 2017. Web. 25 Oct 2020.

Vancouver:

Mittel LB. Efficient Estimation of the Expectation of a Latent Variable in the Presence of Subject-Specific Ancillaries. [Internet] [Doctoral dissertation]. Columbia University; 2017. [cited 2020 Oct 25]. Available from: https://doi.org/10.7916/D8JW8SFB.

Council of Science Editors:

Mittel LB. Efficient Estimation of the Expectation of a Latent Variable in the Presence of Subject-Specific Ancillaries. [Doctoral Dissertation]. Columbia University; 2017. Available from: https://doi.org/10.7916/D8JW8SFB

University of Alberta

5.
Rollins, Curtis.
Exploring Preferences for Poplar Biotechnology and
Integrated Choice *Latent* Variable Models.

Degree: MS, Department of Resource Economics and Environmental Sociology, 2015, University of Alberta

URL: https://era.library.ualberta.ca/files/1n79h7281

► This thesis is divided in two papers, each focusing on a distinct issue. In the first paper (Chapter 2), public preferences for poplar biotechnology are…
(more)

Subjects/Keywords: Latent Variables; Public Preference; Genomics; Choice Model

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APA (6^{th} Edition):

Rollins, C. (2015). Exploring Preferences for Poplar Biotechnology and Integrated Choice Latent Variable Models. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/1n79h7281

Chicago Manual of Style (16^{th} Edition):

Rollins, Curtis. “Exploring Preferences for Poplar Biotechnology and Integrated Choice Latent Variable Models.” 2015. Masters Thesis, University of Alberta. Accessed October 25, 2020. https://era.library.ualberta.ca/files/1n79h7281.

MLA Handbook (7^{th} Edition):

Rollins, Curtis. “Exploring Preferences for Poplar Biotechnology and Integrated Choice Latent Variable Models.” 2015. Web. 25 Oct 2020.

Vancouver:

Rollins C. Exploring Preferences for Poplar Biotechnology and Integrated Choice Latent Variable Models. [Internet] [Masters thesis]. University of Alberta; 2015. [cited 2020 Oct 25]. Available from: https://era.library.ualberta.ca/files/1n79h7281.

Council of Science Editors:

Rollins C. Exploring Preferences for Poplar Biotechnology and Integrated Choice Latent Variable Models. [Masters Thesis]. University of Alberta; 2015. Available from: https://era.library.ualberta.ca/files/1n79h7281

University of Alberta

6. Zaman, Hamid. Investigation of commuting mode choice with respect to TDM policies.

Degree: MS, Department of Civil and Environmental Engineering, 2010, University of Alberta

URL: https://era.library.ualberta.ca/files/g732d971f

► Travel Demand Management (TDM) is now considered one of the most important aspects of transportation planning and operation. The prime objective of TDM is to…
(more)

Subjects/Keywords: TDM; Nested logit; Mode choice; Latent variables

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APA (6^{th} Edition):

Zaman, H. (2010). Investigation of commuting mode choice with respect to TDM policies. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/g732d971f

Chicago Manual of Style (16^{th} Edition):

Zaman, Hamid. “Investigation of commuting mode choice with respect to TDM policies.” 2010. Masters Thesis, University of Alberta. Accessed October 25, 2020. https://era.library.ualberta.ca/files/g732d971f.

MLA Handbook (7^{th} Edition):

Zaman, Hamid. “Investigation of commuting mode choice with respect to TDM policies.” 2010. Web. 25 Oct 2020.

Vancouver:

Zaman H. Investigation of commuting mode choice with respect to TDM policies. [Internet] [Masters thesis]. University of Alberta; 2010. [cited 2020 Oct 25]. Available from: https://era.library.ualberta.ca/files/g732d971f.

Council of Science Editors:

Zaman H. Investigation of commuting mode choice with respect to TDM policies. [Masters Thesis]. University of Alberta; 2010. Available from: https://era.library.ualberta.ca/files/g732d971f

7. Orchard, Peter Raymond. Sparse inverse covariance estimation in Gaussian graphical models.

Degree: PhD, 2014, University of Edinburgh

URL: http://hdl.handle.net/1842/9955

► One of the fundamental tasks in science is to find explainable relationships between observed phenomena. Recent work has addressed this problem by attempting to learn…
(more)

Subjects/Keywords: sparsity; Gaussian; latent variables; copula; GWishart; HMC

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APA (6^{th} Edition):

Orchard, P. R. (2014). Sparse inverse covariance estimation in Gaussian graphical models. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/9955

Chicago Manual of Style (16^{th} Edition):

Orchard, Peter Raymond. “Sparse inverse covariance estimation in Gaussian graphical models.” 2014. Doctoral Dissertation, University of Edinburgh. Accessed October 25, 2020. http://hdl.handle.net/1842/9955.

MLA Handbook (7^{th} Edition):

Orchard, Peter Raymond. “Sparse inverse covariance estimation in Gaussian graphical models.” 2014. Web. 25 Oct 2020.

Vancouver:

Orchard PR. Sparse inverse covariance estimation in Gaussian graphical models. [Internet] [Doctoral dissertation]. University of Edinburgh; 2014. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/1842/9955.

Council of Science Editors:

Orchard PR. Sparse inverse covariance estimation in Gaussian graphical models. [Doctoral Dissertation]. University of Edinburgh; 2014. Available from: http://hdl.handle.net/1842/9955

Arizona State University

8.
Miocevic, Milica.
Statistical Properties of the Single Mediator Model with
*Latent* *Variables* in the Bayesian Framework.

Degree: Psychology, 2017, Arizona State University

URL: http://repository.asu.edu/items/44423

► Statistical mediation analysis has been widely used in the social sciences in order to examine the indirect effects of an independent variable on a dependent…
(more)

Subjects/Keywords: Quantitative psychology; Bayesian; latent variables; mediation analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Miocevic, M. (2017). Statistical Properties of the Single Mediator Model with Latent Variables in the Bayesian Framework. (Doctoral Dissertation). Arizona State University. Retrieved from http://repository.asu.edu/items/44423

Chicago Manual of Style (16^{th} Edition):

Miocevic, Milica. “Statistical Properties of the Single Mediator Model with Latent Variables in the Bayesian Framework.” 2017. Doctoral Dissertation, Arizona State University. Accessed October 25, 2020. http://repository.asu.edu/items/44423.

MLA Handbook (7^{th} Edition):

Miocevic, Milica. “Statistical Properties of the Single Mediator Model with Latent Variables in the Bayesian Framework.” 2017. Web. 25 Oct 2020.

Vancouver:

Miocevic M. Statistical Properties of the Single Mediator Model with Latent Variables in the Bayesian Framework. [Internet] [Doctoral dissertation]. Arizona State University; 2017. [cited 2020 Oct 25]. Available from: http://repository.asu.edu/items/44423.

Council of Science Editors:

Miocevic M. Statistical Properties of the Single Mediator Model with Latent Variables in the Bayesian Framework. [Doctoral Dissertation]. Arizona State University; 2017. Available from: http://repository.asu.edu/items/44423

University of Missouri – Columbia

9. Shireman, Emilie, 1989-. Model selection in mixture modeling.

Degree: 2016, University of Missouri – Columbia

URL: https://doi.org/10.32469/10355/56988

► In the psychological sciences, mixture modeling (also referred to as *latent* class or *latent* profile analysis) is very commonly used to find sub-populations within a…
(more)

Subjects/Keywords: Latent variables; Psychology – Research; Psychology – Statistical methods

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APA (6^{th} Edition):

Shireman, Emilie, 1. (2016). Model selection in mixture modeling. (Thesis). University of Missouri – Columbia. Retrieved from https://doi.org/10.32469/10355/56988

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Shireman, Emilie, 1989-. “Model selection in mixture modeling.” 2016. Thesis, University of Missouri – Columbia. Accessed October 25, 2020. https://doi.org/10.32469/10355/56988.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Shireman, Emilie, 1989-. “Model selection in mixture modeling.” 2016. Web. 25 Oct 2020.

Vancouver:

Shireman, Emilie 1. Model selection in mixture modeling. [Internet] [Thesis]. University of Missouri – Columbia; 2016. [cited 2020 Oct 25]. Available from: https://doi.org/10.32469/10355/56988.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Shireman, Emilie 1. Model selection in mixture modeling. [Thesis]. University of Missouri – Columbia; 2016. Available from: https://doi.org/10.32469/10355/56988

Not specified: Masters Thesis or Doctoral Dissertation

University of California – Riverside

10.
Gray, Jacob.
The Use of Discrete *Latent* *Variables* in Dyadic Data Analysis.

Degree: Psychology, 2018, University of California – Riverside

URL: http://www.escholarship.org/uc/item/57t6k6c1

► Two topics of methodological research in the social sciences that have garnered recent attention are the topics of dyadic data analysis and the use of…
(more)

Subjects/Keywords: Social psychology; Quantitative psychology; couples; dyadic data; latent class; latent variables

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APA (6^{th} Edition):

Gray, J. (2018). The Use of Discrete Latent Variables in Dyadic Data Analysis. (Thesis). University of California – Riverside. Retrieved from http://www.escholarship.org/uc/item/57t6k6c1

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Gray, Jacob. “The Use of Discrete Latent Variables in Dyadic Data Analysis.” 2018. Thesis, University of California – Riverside. Accessed October 25, 2020. http://www.escholarship.org/uc/item/57t6k6c1.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Gray, Jacob. “The Use of Discrete Latent Variables in Dyadic Data Analysis.” 2018. Web. 25 Oct 2020.

Vancouver:

Gray J. The Use of Discrete Latent Variables in Dyadic Data Analysis. [Internet] [Thesis]. University of California – Riverside; 2018. [cited 2020 Oct 25]. Available from: http://www.escholarship.org/uc/item/57t6k6c1.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Gray J. The Use of Discrete Latent Variables in Dyadic Data Analysis. [Thesis]. University of California – Riverside; 2018. Available from: http://www.escholarship.org/uc/item/57t6k6c1

Not specified: Masters Thesis or Doctoral Dissertation

Columbia University

11.
Liu, Xiang.
Three Contributions to *Latent* Variable Modeling.

Degree: 2019, Columbia University

URL: https://doi.org/10.7916/D8Q25H61

► The dissertation includes three papers that address some theoretical and technical issues of *latent* variable models. The first paper extends the uniformly most powerful test…
(more)

Subjects/Keywords: Educational tests and measurements; Statistics; Latent structure analysis; Latent variables

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APA (6^{th} Edition):

Liu, X. (2019). Three Contributions to Latent Variable Modeling. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8Q25H61

Chicago Manual of Style (16^{th} Edition):

Liu, Xiang. “Three Contributions to Latent Variable Modeling.” 2019. Doctoral Dissertation, Columbia University. Accessed October 25, 2020. https://doi.org/10.7916/D8Q25H61.

MLA Handbook (7^{th} Edition):

Liu, Xiang. “Three Contributions to Latent Variable Modeling.” 2019. Web. 25 Oct 2020.

Vancouver:

Liu X. Three Contributions to Latent Variable Modeling. [Internet] [Doctoral dissertation]. Columbia University; 2019. [cited 2020 Oct 25]. Available from: https://doi.org/10.7916/D8Q25H61.

Council of Science Editors:

Liu X. Three Contributions to Latent Variable Modeling. [Doctoral Dissertation]. Columbia University; 2019. Available from: https://doi.org/10.7916/D8Q25H61

Brigham Young University

12. Pyper, Jordan Daniel. Estimation of the Effects of Parental Measures on Child Aggression Using Structural Equation Modeling.

Degree: MS, 2012, Brigham Young University

URL: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=4240&context=etd

► A child's parents are the primary source of knowledge and learned behaviors for developing children, and the benefits or repercussions of certain parental practices can…
(more)

Subjects/Keywords: latent variables; manifest variables; structural equation modeling; Bayesian methods; Frequentist methods; Statistics and Probability

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APA (6^{th} Edition):

Pyper, J. D. (2012). Estimation of the Effects of Parental Measures on Child Aggression Using Structural Equation Modeling. (Masters Thesis). Brigham Young University. Retrieved from https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=4240&context=etd

Chicago Manual of Style (16^{th} Edition):

Pyper, Jordan Daniel. “Estimation of the Effects of Parental Measures on Child Aggression Using Structural Equation Modeling.” 2012. Masters Thesis, Brigham Young University. Accessed October 25, 2020. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=4240&context=etd.

MLA Handbook (7^{th} Edition):

Pyper, Jordan Daniel. “Estimation of the Effects of Parental Measures on Child Aggression Using Structural Equation Modeling.” 2012. Web. 25 Oct 2020.

Vancouver:

Pyper JD. Estimation of the Effects of Parental Measures on Child Aggression Using Structural Equation Modeling. [Internet] [Masters thesis]. Brigham Young University; 2012. [cited 2020 Oct 25]. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=4240&context=etd.

Council of Science Editors:

Pyper JD. Estimation of the Effects of Parental Measures on Child Aggression Using Structural Equation Modeling. [Masters Thesis]. Brigham Young University; 2012. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=4240&context=etd

Universitat Politècnica de València

13. Vidal Puig, Santiago. FAULT DIAGNOSIS TOOLS IN MULTIVARIATE STATISTICAL PROCESS AND QUALITY CONTROL .

Degree: 2016, Universitat Politècnica de València

URL: http://hdl.handle.net/10251/61292

► [EN] An accurate fault diagnosis of both, faults sensors and real process faults have become more and more important for process monitoring (minimize downtime, increase…
(more)

Subjects/Keywords: Fault Diagnosis; Statistical Process Monitoring; Latent variables; FDI; MSPC; MSQC

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APA (6^{th} Edition):

Vidal Puig, S. (2016). FAULT DIAGNOSIS TOOLS IN MULTIVARIATE STATISTICAL PROCESS AND QUALITY CONTROL . (Doctoral Dissertation). Universitat Politècnica de València. Retrieved from http://hdl.handle.net/10251/61292

Chicago Manual of Style (16^{th} Edition):

Vidal Puig, Santiago. “FAULT DIAGNOSIS TOOLS IN MULTIVARIATE STATISTICAL PROCESS AND QUALITY CONTROL .” 2016. Doctoral Dissertation, Universitat Politècnica de València. Accessed October 25, 2020. http://hdl.handle.net/10251/61292.

MLA Handbook (7^{th} Edition):

Vidal Puig, Santiago. “FAULT DIAGNOSIS TOOLS IN MULTIVARIATE STATISTICAL PROCESS AND QUALITY CONTROL .” 2016. Web. 25 Oct 2020.

Vancouver:

Vidal Puig S. FAULT DIAGNOSIS TOOLS IN MULTIVARIATE STATISTICAL PROCESS AND QUALITY CONTROL . [Internet] [Doctoral dissertation]. Universitat Politècnica de València; 2016. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/10251/61292.

Council of Science Editors:

Vidal Puig S. FAULT DIAGNOSIS TOOLS IN MULTIVARIATE STATISTICAL PROCESS AND QUALITY CONTROL . [Doctoral Dissertation]. Universitat Politècnica de València; 2016. Available from: http://hdl.handle.net/10251/61292

University of Guelph

14. Tang, Yang. Model-based clustering of high-dimensional binary data.

Degree: MS, Department of Mathematics and Statistics, 2013, University of Guelph

URL: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/7458

► We present a mixture of *latent* trait models with common slope parameters (MCLT) for high dimensional binary data, a data type for which few established…
(more)

Subjects/Keywords: binary data; clustering; high dimension; latent variables; mixture models

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APA (6^{th} Edition):

Tang, Y. (2013). Model-based clustering of high-dimensional binary data. (Masters Thesis). University of Guelph. Retrieved from https://atrium.lib.uoguelph.ca/xmlui/handle/10214/7458

Chicago Manual of Style (16^{th} Edition):

Tang, Yang. “Model-based clustering of high-dimensional binary data.” 2013. Masters Thesis, University of Guelph. Accessed October 25, 2020. https://atrium.lib.uoguelph.ca/xmlui/handle/10214/7458.

MLA Handbook (7^{th} Edition):

Tang, Yang. “Model-based clustering of high-dimensional binary data.” 2013. Web. 25 Oct 2020.

Vancouver:

Tang Y. Model-based clustering of high-dimensional binary data. [Internet] [Masters thesis]. University of Guelph; 2013. [cited 2020 Oct 25]. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/7458.

Council of Science Editors:

Tang Y. Model-based clustering of high-dimensional binary data. [Masters Thesis]. University of Guelph; 2013. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/7458

Colorado State University

15. Schliep, Erin M. Spatial probit models for multivariate ordinal data: computational efficiency and parameter identifiability.

Degree: PhD, Statistics, 2013, Colorado State University

URL: http://hdl.handle.net/10217/80174

► The Colorado Natural Heritage Program (CNHP) at Colorado State University evaluates Colorado's rare and at-risk species and habitats and promotes conservation of biological resources. One…
(more)

Subjects/Keywords: Bayesian; identifiability; latent variables; ordinal data; probit; spatial

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APA (6^{th} Edition):

Schliep, E. M. (2013). Spatial probit models for multivariate ordinal data: computational efficiency and parameter identifiability. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/80174

Chicago Manual of Style (16^{th} Edition):

Schliep, Erin M. “Spatial probit models for multivariate ordinal data: computational efficiency and parameter identifiability.” 2013. Doctoral Dissertation, Colorado State University. Accessed October 25, 2020. http://hdl.handle.net/10217/80174.

MLA Handbook (7^{th} Edition):

Schliep, Erin M. “Spatial probit models for multivariate ordinal data: computational efficiency and parameter identifiability.” 2013. Web. 25 Oct 2020.

Vancouver:

Schliep EM. Spatial probit models for multivariate ordinal data: computational efficiency and parameter identifiability. [Internet] [Doctoral dissertation]. Colorado State University; 2013. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/10217/80174.

Council of Science Editors:

Schliep EM. Spatial probit models for multivariate ordinal data: computational efficiency and parameter identifiability. [Doctoral Dissertation]. Colorado State University; 2013. Available from: http://hdl.handle.net/10217/80174

Hong Kong University of Science and Technology

16.
Wang, Yi.
* Latent* tree models for multivariate density estimation : algorithms and applications.

Degree: 2009, Hong Kong University of Science and Technology

URL: http://repository.ust.hk/ir/Record/1783.1-6323 ; https://doi.org/10.14711/thesis-b1070815 ; http://repository.ust.hk/ir/bitstream/1783.1-6323/1/th_redirect.html

► Multivariate density estimation is a fundamental problem in Applied Statistics and Machine Learning. Given a collection of data sampled from an unknown distribution, the task…
(more)

Subjects/Keywords: Multivariate analysis ; Latent variables

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Wang, Y. (2009). Latent tree models for multivariate density estimation : algorithms and applications. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-6323 ; https://doi.org/10.14711/thesis-b1070815 ; http://repository.ust.hk/ir/bitstream/1783.1-6323/1/th_redirect.html

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Wang, Yi. “Latent tree models for multivariate density estimation : algorithms and applications.” 2009. Thesis, Hong Kong University of Science and Technology. Accessed October 25, 2020. http://repository.ust.hk/ir/Record/1783.1-6323 ; https://doi.org/10.14711/thesis-b1070815 ; http://repository.ust.hk/ir/bitstream/1783.1-6323/1/th_redirect.html.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Wang, Yi. “Latent tree models for multivariate density estimation : algorithms and applications.” 2009. Web. 25 Oct 2020.

Vancouver:

Wang Y. Latent tree models for multivariate density estimation : algorithms and applications. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2009. [cited 2020 Oct 25]. Available from: http://repository.ust.hk/ir/Record/1783.1-6323 ; https://doi.org/10.14711/thesis-b1070815 ; http://repository.ust.hk/ir/bitstream/1783.1-6323/1/th_redirect.html.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wang Y. Latent tree models for multivariate density estimation : algorithms and applications. [Thesis]. Hong Kong University of Science and Technology; 2009. Available from: http://repository.ust.hk/ir/Record/1783.1-6323 ; https://doi.org/10.14711/thesis-b1070815 ; http://repository.ust.hk/ir/bitstream/1783.1-6323/1/th_redirect.html

Not specified: Masters Thesis or Doctoral Dissertation

University of Melbourne

17. de Araujo, Luis Fernando Silva Castro. Dimensional constructs and methods for their treatment in psychiatry research.

Degree: 2018, University of Melbourne

URL: http://hdl.handle.net/11343/211685

► Psychiatry has lagged behind other fields within the cognitive sciences regarding the analysis of dimensional constructs. This has surely improved recently by diagnostic classifications’ organisation…
(more)

Subjects/Keywords: psychiatry; latent variables; structural equation model; philosophy of psychiatry

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

de Araujo, L. F. S. C. (2018). Dimensional constructs and methods for their treatment in psychiatry research. (Doctoral Dissertation). University of Melbourne. Retrieved from http://hdl.handle.net/11343/211685

Chicago Manual of Style (16^{th} Edition):

de Araujo, Luis Fernando Silva Castro. “Dimensional constructs and methods for their treatment in psychiatry research.” 2018. Doctoral Dissertation, University of Melbourne. Accessed October 25, 2020. http://hdl.handle.net/11343/211685.

MLA Handbook (7^{th} Edition):

de Araujo, Luis Fernando Silva Castro. “Dimensional constructs and methods for their treatment in psychiatry research.” 2018. Web. 25 Oct 2020.

Vancouver:

de Araujo LFSC. Dimensional constructs and methods for their treatment in psychiatry research. [Internet] [Doctoral dissertation]. University of Melbourne; 2018. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/11343/211685.

Council of Science Editors:

de Araujo LFSC. Dimensional constructs and methods for their treatment in psychiatry research. [Doctoral Dissertation]. University of Melbourne; 2018. Available from: http://hdl.handle.net/11343/211685

University of Waterloo

18. Fang, Yizhou. Computationally Efficient Multi-Asset Stochastic Volatility Modeling.

Degree: 2018, University of Waterloo

URL: http://hdl.handle.net/10012/13663

► Stochastic volatility (SV) models are popular in financial modeling, because they capture the inherent uncertainty of the asset volatility. Since assets are observed to co-move…
(more)

Subjects/Keywords: Bayesian Inference; Stochastic Volatility; Latent Variables; Multiple Assets

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Fang, Y. (2018). Computationally Efficient Multi-Asset Stochastic Volatility Modeling. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/13663

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Fang, Yizhou. “Computationally Efficient Multi-Asset Stochastic Volatility Modeling.” 2018. Thesis, University of Waterloo. Accessed October 25, 2020. http://hdl.handle.net/10012/13663.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Fang, Yizhou. “Computationally Efficient Multi-Asset Stochastic Volatility Modeling.” 2018. Web. 25 Oct 2020.

Vancouver:

Fang Y. Computationally Efficient Multi-Asset Stochastic Volatility Modeling. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/10012/13663.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Fang Y. Computationally Efficient Multi-Asset Stochastic Volatility Modeling. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/13663

Not specified: Masters Thesis or Doctoral Dissertation

Princeton University

19.
Cabreros, Irineo C.
* Latent* Variable Modeling and Causal Inference in Population-Structured Genetics
.

Degree: PhD, 2020, Princeton University

URL: http://arks.princeton.edu/ark:/88435/dsp01x920g081v

► Nonrandomly mating populations, referred to as structured populations, are commonly encountered in genetic studies. A common characteristic of structured populations is that separate subpopulations differ…
(more)

Subjects/Keywords: Causal Inference; Latent Variables; Population Genetics; Population Structure; Statistical Genetics; Statistics

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Cabreros, I. C. (2020). Latent Variable Modeling and Causal Inference in Population-Structured Genetics . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01x920g081v

Chicago Manual of Style (16^{th} Edition):

Cabreros, Irineo C. “Latent Variable Modeling and Causal Inference in Population-Structured Genetics .” 2020. Doctoral Dissertation, Princeton University. Accessed October 25, 2020. http://arks.princeton.edu/ark:/88435/dsp01x920g081v.

MLA Handbook (7^{th} Edition):

Cabreros, Irineo C. “Latent Variable Modeling and Causal Inference in Population-Structured Genetics .” 2020. Web. 25 Oct 2020.

Vancouver:

Cabreros IC. Latent Variable Modeling and Causal Inference in Population-Structured Genetics . [Internet] [Doctoral dissertation]. Princeton University; 2020. [cited 2020 Oct 25]. Available from: http://arks.princeton.edu/ark:/88435/dsp01x920g081v.

Council of Science Editors:

Cabreros IC. Latent Variable Modeling and Causal Inference in Population-Structured Genetics . [Doctoral Dissertation]. Princeton University; 2020. Available from: http://arks.princeton.edu/ark:/88435/dsp01x920g081v

Hong Kong University of Science and Technology

20.
Chen, Tao.
Search-based learning of *latent* tree models.

Degree: 2009, Hong Kong University of Science and Technology

URL: http://repository.ust.hk/ir/Record/1783.1-5953 ; https://doi.org/10.14711/thesis-b1041208 ; http://repository.ust.hk/ir/bitstream/1783.1-5953/1/th_redirect.html

► A *latent* variable model is a statistical model that relates a set of observed *variables* (aka manifest *variables*) to a set of unobserved *variables* (aka…
(more)

Subjects/Keywords: Latent structure analysis ; Latent variables ; Search theory ; Algorithms

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Chen, T. (2009). Search-based learning of latent tree models. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-5953 ; https://doi.org/10.14711/thesis-b1041208 ; http://repository.ust.hk/ir/bitstream/1783.1-5953/1/th_redirect.html

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Chen, Tao. “Search-based learning of latent tree models.” 2009. Thesis, Hong Kong University of Science and Technology. Accessed October 25, 2020. http://repository.ust.hk/ir/Record/1783.1-5953 ; https://doi.org/10.14711/thesis-b1041208 ; http://repository.ust.hk/ir/bitstream/1783.1-5953/1/th_redirect.html.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Chen, Tao. “Search-based learning of latent tree models.” 2009. Web. 25 Oct 2020.

Vancouver:

Chen T. Search-based learning of latent tree models. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2009. [cited 2020 Oct 25]. Available from: http://repository.ust.hk/ir/Record/1783.1-5953 ; https://doi.org/10.14711/thesis-b1041208 ; http://repository.ust.hk/ir/bitstream/1783.1-5953/1/th_redirect.html.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chen T. Search-based learning of latent tree models. [Thesis]. Hong Kong University of Science and Technology; 2009. Available from: http://repository.ust.hk/ir/Record/1783.1-5953 ; https://doi.org/10.14711/thesis-b1041208 ; http://repository.ust.hk/ir/bitstream/1783.1-5953/1/th_redirect.html

Not specified: Masters Thesis or Doctoral Dissertation

University of South Carolina

21. Liang, Yawei. Cluster Analysis of Mixed-Mode Data.

Degree: PhD, Statistics, 2019, University of South Carolina

URL: https://scholarcommons.sc.edu/etd/5305

► In the modern world, data have become increasingly more complex and often contain different types of features. Two very common types of features are…
(more)

Subjects/Keywords: Statistics and Probability; continuous variables; discrete variables; Clustering mixed-mode data; latent realization method; finite mixture model

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Liang, Y. (2019). Cluster Analysis of Mixed-Mode Data. (Doctoral Dissertation). University of South Carolina. Retrieved from https://scholarcommons.sc.edu/etd/5305

Chicago Manual of Style (16^{th} Edition):

Liang, Yawei. “Cluster Analysis of Mixed-Mode Data.” 2019. Doctoral Dissertation, University of South Carolina. Accessed October 25, 2020. https://scholarcommons.sc.edu/etd/5305.

MLA Handbook (7^{th} Edition):

Liang, Yawei. “Cluster Analysis of Mixed-Mode Data.” 2019. Web. 25 Oct 2020.

Vancouver:

Liang Y. Cluster Analysis of Mixed-Mode Data. [Internet] [Doctoral dissertation]. University of South Carolina; 2019. [cited 2020 Oct 25]. Available from: https://scholarcommons.sc.edu/etd/5305.

Council of Science Editors:

Liang Y. Cluster Analysis of Mixed-Mode Data. [Doctoral Dissertation]. University of South Carolina; 2019. Available from: https://scholarcommons.sc.edu/etd/5305

University of California – Berkeley

22. Petrov, Slav Orlinov. Coarse-to-Fine Natural Language Processing.

Degree: Computer Science, 2009, University of California – Berkeley

URL: http://www.escholarship.org/uc/item/8kp924f2

► State-of-the-art natural language processing models are anything but compact. Syntactic parsers have huge grammars, machine translation systems have huge transfer tables, and so on across…
(more)

Subjects/Keywords: Computer Science; Artificial Intelligence; Latent Variables; Machine Learning; Machine Translation; Natural Language Processing; Parsing; Speech

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Petrov, S. O. (2009). Coarse-to-Fine Natural Language Processing. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/8kp924f2

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Petrov, Slav Orlinov. “Coarse-to-Fine Natural Language Processing.” 2009. Thesis, University of California – Berkeley. Accessed October 25, 2020. http://www.escholarship.org/uc/item/8kp924f2.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Petrov, Slav Orlinov. “Coarse-to-Fine Natural Language Processing.” 2009. Web. 25 Oct 2020.

Vancouver:

Petrov SO. Coarse-to-Fine Natural Language Processing. [Internet] [Thesis]. University of California – Berkeley; 2009. [cited 2020 Oct 25]. Available from: http://www.escholarship.org/uc/item/8kp924f2.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Petrov SO. Coarse-to-Fine Natural Language Processing. [Thesis]. University of California – Berkeley; 2009. Available from: http://www.escholarship.org/uc/item/8kp924f2

Not specified: Masters Thesis or Doctoral Dissertation

Universidade Estadual de Campinas

23.
Costa, Denise Reis, 1985-.
Estimação robusta em modelos de variáveis latentes para dados censurados: Robust estimation in *latent* variable models for censored data.

Degree: 2013, Universidade Estadual de Campinas

URL: http://repositorio.unicamp.br/jspui/handle/REPOSIP/306683

► Abstract: *Latent* variable models are broadly used by psychometrists, econometrists and social science researchers to model *variables* that cannnot be directly measured, known as constructs…
(more)

Subjects/Keywords: Variáveis latentes; Estimativa de parâmetro; Métodos estatísticos robustos; Latent variables; Parameter estimation; Robust statistical methods

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Costa, Denise Reis, 1. (2013). Estimação robusta em modelos de variáveis latentes para dados censurados: Robust estimation in latent variable models for censored data. (Thesis). Universidade Estadual de Campinas. Retrieved from http://repositorio.unicamp.br/jspui/handle/REPOSIP/306683

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Costa, Denise Reis, 1985-. “Estimação robusta em modelos de variáveis latentes para dados censurados: Robust estimation in latent variable models for censored data.” 2013. Thesis, Universidade Estadual de Campinas. Accessed October 25, 2020. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306683.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Costa, Denise Reis, 1985-. “Estimação robusta em modelos de variáveis latentes para dados censurados: Robust estimation in latent variable models for censored data.” 2013. Web. 25 Oct 2020.

Vancouver:

Costa, Denise Reis 1. Estimação robusta em modelos de variáveis latentes para dados censurados: Robust estimation in latent variable models for censored data. [Internet] [Thesis]. Universidade Estadual de Campinas; 2013. [cited 2020 Oct 25]. Available from: http://repositorio.unicamp.br/jspui/handle/REPOSIP/306683.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Costa, Denise Reis 1. Estimação robusta em modelos de variáveis latentes para dados censurados: Robust estimation in latent variable models for censored data. [Thesis]. Universidade Estadual de Campinas; 2013. Available from: http://repositorio.unicamp.br/jspui/handle/REPOSIP/306683

Not specified: Masters Thesis or Doctoral Dissertation

Columbia University

24.
Fang, Guanhua.
* Latent* Variable Models in Measurement: Theory and Application.

Degree: 2020, Columbia University

URL: https://doi.org/10.7916/d8-gghx-v227

► *Latent* variable models play an important role in educational and psychological measurement, where items are presented to individuals, resulting in item response data. Such data…
(more)

Subjects/Keywords: Statistics; Latent variables; Mathematical models; Psychometrics – Mathematical models; Educational tests and measurements

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Fang, G. (2020). Latent Variable Models in Measurement: Theory and Application. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/d8-gghx-v227

Chicago Manual of Style (16^{th} Edition):

Fang, Guanhua. “Latent Variable Models in Measurement: Theory and Application.” 2020. Doctoral Dissertation, Columbia University. Accessed October 25, 2020. https://doi.org/10.7916/d8-gghx-v227.

MLA Handbook (7^{th} Edition):

Fang, Guanhua. “Latent Variable Models in Measurement: Theory and Application.” 2020. Web. 25 Oct 2020.

Vancouver:

Fang G. Latent Variable Models in Measurement: Theory and Application. [Internet] [Doctoral dissertation]. Columbia University; 2020. [cited 2020 Oct 25]. Available from: https://doi.org/10.7916/d8-gghx-v227.

Council of Science Editors:

Fang G. Latent Variable Models in Measurement: Theory and Application. [Doctoral Dissertation]. Columbia University; 2020. Available from: https://doi.org/10.7916/d8-gghx-v227

Columbia University

25.
Han, Zhuangzhuang.
Three New Studies on Model-data Fit for *Latent* Variable Models in Educational Measurement.

Degree: 2019, Columbia University

URL: https://doi.org/10.7916/d8-b6wk-6339

► This dissertation encompasses three studies on issues of model-data fit methods for *latent* variable models implemented in modern educational measurement. The first study proposes a…
(more)

Subjects/Keywords: Educational tests and measurements; Latent variables; Statistics; Educational tests and measurements – Mathematical models

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Han, Z. (2019). Three New Studies on Model-data Fit for Latent Variable Models in Educational Measurement. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/d8-b6wk-6339

Chicago Manual of Style (16^{th} Edition):

Han, Zhuangzhuang. “Three New Studies on Model-data Fit for Latent Variable Models in Educational Measurement.” 2019. Doctoral Dissertation, Columbia University. Accessed October 25, 2020. https://doi.org/10.7916/d8-b6wk-6339.

MLA Handbook (7^{th} Edition):

Han, Zhuangzhuang. “Three New Studies on Model-data Fit for Latent Variable Models in Educational Measurement.” 2019. Web. 25 Oct 2020.

Vancouver:

Han Z. Three New Studies on Model-data Fit for Latent Variable Models in Educational Measurement. [Internet] [Doctoral dissertation]. Columbia University; 2019. [cited 2020 Oct 25]. Available from: https://doi.org/10.7916/d8-b6wk-6339.

Council of Science Editors:

Han Z. Three New Studies on Model-data Fit for Latent Variable Models in Educational Measurement. [Doctoral Dissertation]. Columbia University; 2019. Available from: https://doi.org/10.7916/d8-b6wk-6339

University of Washington

26. Beam, Colin Stuart. Models of human causal learning: review, synthesis, generalization. (A long argument for a short rule).

Degree: PhD, 2017, University of Washington

URL: http://hdl.handle.net/1773/38679

► This dissertation is composed of three major components. The first reviews models of causal learning with special emphasis given to Bayesian approaches. The second component…
(more)

Subjects/Keywords: Bayesian models; causal learning; heuristics; latent variables; levels of analysis; Cognitive psychology; Psychology

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Beam, C. S. (2017). Models of human causal learning: review, synthesis, generalization. (A long argument for a short rule). (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/38679

Chicago Manual of Style (16^{th} Edition):

Beam, Colin Stuart. “Models of human causal learning: review, synthesis, generalization. (A long argument for a short rule).” 2017. Doctoral Dissertation, University of Washington. Accessed October 25, 2020. http://hdl.handle.net/1773/38679.

MLA Handbook (7^{th} Edition):

Beam, Colin Stuart. “Models of human causal learning: review, synthesis, generalization. (A long argument for a short rule).” 2017. Web. 25 Oct 2020.

Vancouver:

Beam CS. Models of human causal learning: review, synthesis, generalization. (A long argument for a short rule). [Internet] [Doctoral dissertation]. University of Washington; 2017. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/1773/38679.

Council of Science Editors:

Beam CS. Models of human causal learning: review, synthesis, generalization. (A long argument for a short rule). [Doctoral Dissertation]. University of Washington; 2017. Available from: http://hdl.handle.net/1773/38679

New Jersey Institute of Technology

27.
Aalderks, Daniel Richard.
Using *latent* semantic analysis to detect non-cognitive *variables* of academic performance.

Degree: MSin Professional and Technical Communication - (M.S.), Humanities, 2014, New Jersey Institute of Technology

URL: https://digitalcommons.njit.edu/theses/181

► This thesis explores the possibilities of using *latent* semantic analysis to detect evidence of intrapersonal personality *variables* in post-secondary student essays. Determining student achievement…
(more)

Subjects/Keywords: Latent semantic analysis; Student achievement; Non-cognitive variables; Technical and Professional Writing

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Aalderks, D. R. (2014). Using latent semantic analysis to detect non-cognitive variables of academic performance. (Thesis). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/theses/181

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Aalderks, Daniel Richard. “Using latent semantic analysis to detect non-cognitive variables of academic performance.” 2014. Thesis, New Jersey Institute of Technology. Accessed October 25, 2020. https://digitalcommons.njit.edu/theses/181.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Aalderks, Daniel Richard. “Using latent semantic analysis to detect non-cognitive variables of academic performance.” 2014. Web. 25 Oct 2020.

Vancouver:

Aalderks DR. Using latent semantic analysis to detect non-cognitive variables of academic performance. [Internet] [Thesis]. New Jersey Institute of Technology; 2014. [cited 2020 Oct 25]. Available from: https://digitalcommons.njit.edu/theses/181.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Aalderks DR. Using latent semantic analysis to detect non-cognitive variables of academic performance. [Thesis]. New Jersey Institute of Technology; 2014. Available from: https://digitalcommons.njit.edu/theses/181

Not specified: Masters Thesis or Doctoral Dissertation

Duquesne University

28. Maldonado, Hernan. Bayesian Regression Inference Using a Normal Mixture Model.

Degree: MS, Computational Mathematics, 2012, Duquesne University

URL: https://dsc.duq.edu/etd/859

► In this thesis we develop a two component mixture model to perform a Bayesian regression. We implement our model computationally using the Gibbs sampler algorithm…
(more)

Subjects/Keywords: Bayesian regression; Gibbs sampler; Label switching problem; Latent variables; Mixture models; Two component

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Maldonado, H. (2012). Bayesian Regression Inference Using a Normal Mixture Model. (Masters Thesis). Duquesne University. Retrieved from https://dsc.duq.edu/etd/859

Chicago Manual of Style (16^{th} Edition):

Maldonado, Hernan. “Bayesian Regression Inference Using a Normal Mixture Model.” 2012. Masters Thesis, Duquesne University. Accessed October 25, 2020. https://dsc.duq.edu/etd/859.

MLA Handbook (7^{th} Edition):

Maldonado, Hernan. “Bayesian Regression Inference Using a Normal Mixture Model.” 2012. Web. 25 Oct 2020.

Vancouver:

Maldonado H. Bayesian Regression Inference Using a Normal Mixture Model. [Internet] [Masters thesis]. Duquesne University; 2012. [cited 2020 Oct 25]. Available from: https://dsc.duq.edu/etd/859.

Council of Science Editors:

Maldonado H. Bayesian Regression Inference Using a Normal Mixture Model. [Masters Thesis]. Duquesne University; 2012. Available from: https://dsc.duq.edu/etd/859

University of Missouri – Columbia

29.
Su, Ihui.
Passage-related local item dependence and spurious *latent* classes in the mixture Rasch model : a simulation study.

Degree: 2013, University of Missouri – Columbia

URL: https://doi.org/10.32469/10355/43138

► [ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Mixture Rasch models, which are often used to investigate response strategy difference, differential item functioning,…
(more)

Subjects/Keywords: Educational statistics; Mixtures – Statistical methods; Latent variables; Rasch models; Educational tests and measurements

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Su, I. (2013). Passage-related local item dependence and spurious latent classes in the mixture Rasch model : a simulation study. (Thesis). University of Missouri – Columbia. Retrieved from https://doi.org/10.32469/10355/43138

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Su, Ihui. “Passage-related local item dependence and spurious latent classes in the mixture Rasch model : a simulation study.” 2013. Thesis, University of Missouri – Columbia. Accessed October 25, 2020. https://doi.org/10.32469/10355/43138.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Su, Ihui. “Passage-related local item dependence and spurious latent classes in the mixture Rasch model : a simulation study.” 2013. Web. 25 Oct 2020.

Vancouver:

Su I. Passage-related local item dependence and spurious latent classes in the mixture Rasch model : a simulation study. [Internet] [Thesis]. University of Missouri – Columbia; 2013. [cited 2020 Oct 25]. Available from: https://doi.org/10.32469/10355/43138.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Su I. Passage-related local item dependence and spurious latent classes in the mixture Rasch model : a simulation study. [Thesis]. University of Missouri – Columbia; 2013. Available from: https://doi.org/10.32469/10355/43138

Not specified: Masters Thesis or Doctoral Dissertation

University of North Texas

30.
Granado, Elvalicia A.
Comparing Three Effect Sizes for *Latent* Class Analysis.

Degree: 2015, University of North Texas

URL: https://digital.library.unt.edu/ark:/67531/metadc822835/

► Traditional *latent* class analysis (LCA) considers entropy R2 as the only measure of effect size. However, entropy may not always be reliable, a low boundary…
(more)

Subjects/Keywords: latent class analysis; effect size; entropy R2; I-index; Cohen’s d; classification accuracy; Monte Carlo study; Latent structure analysis.; Latent variables.; Effect sizes (Statistics); Error analysis (Mathematics)

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Granado, E. A. (2015). Comparing Three Effect Sizes for Latent Class Analysis. (Thesis). University of North Texas. Retrieved from https://digital.library.unt.edu/ark:/67531/metadc822835/

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Granado, Elvalicia A. “Comparing Three Effect Sizes for Latent Class Analysis.” 2015. Thesis, University of North Texas. Accessed October 25, 2020. https://digital.library.unt.edu/ark:/67531/metadc822835/.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Granado, Elvalicia A. “Comparing Three Effect Sizes for Latent Class Analysis.” 2015. Web. 25 Oct 2020.

Vancouver:

Granado EA. Comparing Three Effect Sizes for Latent Class Analysis. [Internet] [Thesis]. University of North Texas; 2015. [cited 2020 Oct 25]. Available from: https://digital.library.unt.edu/ark:/67531/metadc822835/.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Granado EA. Comparing Three Effect Sizes for Latent Class Analysis. [Thesis]. University of North Texas; 2015. Available from: https://digital.library.unt.edu/ark:/67531/metadc822835/

Not specified: Masters Thesis or Doctoral Dissertation