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University: UCLA

You searched for subject:(imputation). Showing records 1 – 10 of 10 total matches.

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1. Jeffries, Robin Angela. Sequential Bayesian Regression for Multiple Imputation and Conditional Editing.

Degree: Biostatistics, 2013, UCLA

 Analysts faced with errors in data apply editing rules to fix erroneous data. These edits are deterministically assigned and edits may not be correct in… (more)

Subjects/Keywords: Biostatistics; Bayesian; Editing; Imputation

…Computing . . . . . . . . . . . . . . . . . . . . 18 3 Review of Editing and Imputation… …Procedures . . . . . . . . . . . . . . . . 22 3.1 22 3.1.1 3.2 Imputation… …Multiple Imputation . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Notation… …26 v 3.2.1 Sequential Regression Multivariate Imputation . . . . . . . . . . . . . 26… …29 3.4 Combining Edit & Imputation… 

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

APA (6th Edition):

Jeffries, R. A. (2013). Sequential Bayesian Regression for Multiple Imputation and Conditional Editing. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/0171h183

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):

Jeffries, Robin Angela. “Sequential Bayesian Regression for Multiple Imputation and Conditional Editing.” 2013. Thesis, UCLA. Accessed December 08, 2019. http://www.escholarship.org/uc/item/0171h183.

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

MLA Handbook (7th Edition):

Jeffries, Robin Angela. “Sequential Bayesian Regression for Multiple Imputation and Conditional Editing.” 2013. Web. 08 Dec 2019.

Vancouver:

Jeffries RA. Sequential Bayesian Regression for Multiple Imputation and Conditional Editing. [Internet] [Thesis]. UCLA; 2013. [cited 2019 Dec 08]. Available from: http://www.escholarship.org/uc/item/0171h183.

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

Council of Science Editors:

Jeffries RA. Sequential Bayesian Regression for Multiple Imputation and Conditional Editing. [Thesis]. UCLA; 2013. Available from: http://www.escholarship.org/uc/item/0171h183

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


UCLA

2. Keller, Brian Tinnell. Model-Based Imputation for Multilevel Interaction Effects.

Degree: Psychology, 2019, UCLA

 Over the last few decades, a large body of research supports the use of multiple imputation as a method for handling missing data. Despite imputation’s… (more)

Subjects/Keywords: Quantitative psychology; Statistics; Blimp; Imputation; Interactions; Missing Data; Multilevel Models

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APA (6th Edition):

Keller, B. T. (2019). Model-Based Imputation for Multilevel Interaction Effects. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/0mh203nn

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):

Keller, Brian Tinnell. “Model-Based Imputation for Multilevel Interaction Effects.” 2019. Thesis, UCLA. Accessed December 08, 2019. http://www.escholarship.org/uc/item/0mh203nn.

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

MLA Handbook (7th Edition):

Keller, Brian Tinnell. “Model-Based Imputation for Multilevel Interaction Effects.” 2019. Web. 08 Dec 2019.

Vancouver:

Keller BT. Model-Based Imputation for Multilevel Interaction Effects. [Internet] [Thesis]. UCLA; 2019. [cited 2019 Dec 08]. Available from: http://www.escholarship.org/uc/item/0mh203nn.

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

Council of Science Editors:

Keller BT. Model-Based Imputation for Multilevel Interaction Effects. [Thesis]. UCLA; 2019. Available from: http://www.escholarship.org/uc/item/0mh203nn

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


UCLA

3. Li, Fanghua. Three Essays on Labor Economics.

Degree: Economics, 2018, UCLA

 This thesis contribute towards the understanding of labor economics and applied econometrics; the thesis is made up of three chapters.The first chapter explores the causal… (more)

Subjects/Keywords: Economics; Conditional Moment Restrictions; Data combination; imputation; Misallocation; Occupational Mobility; partial insurance

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APA (6th Edition):

Li, F. (2018). Three Essays on Labor Economics. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/4qh3k7d9

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):

Li, Fanghua. “Three Essays on Labor Economics.” 2018. Thesis, UCLA. Accessed December 08, 2019. http://www.escholarship.org/uc/item/4qh3k7d9.

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

MLA Handbook (7th Edition):

Li, Fanghua. “Three Essays on Labor Economics.” 2018. Web. 08 Dec 2019.

Vancouver:

Li F. Three Essays on Labor Economics. [Internet] [Thesis]. UCLA; 2018. [cited 2019 Dec 08]. Available from: http://www.escholarship.org/uc/item/4qh3k7d9.

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

Council of Science Editors:

Li F. Three Essays on Labor Economics. [Thesis]. UCLA; 2018. Available from: http://www.escholarship.org/uc/item/4qh3k7d9

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


UCLA

4. Yi, Yi. A Drug-Dependence Treatment Medication Analysis based on Longitudinal Data with Missing Values using Multiple-Imputation Generalized Estimating Equations.

Degree: Statistics, 2014, UCLA

 Repeated-Measures longitudinal data is common in drug research, where every patient is repeatedly measured across time. Responses could either be continuous variables such as blood… (more)

Subjects/Keywords: Statistics; Pharmaceutical sciences; Biostatistics; Bupropion; Generalized Estimating Equations; Longitudinal Data; Multiple Imputation; Repeated Measures

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APA (6th Edition):

Yi, Y. (2014). A Drug-Dependence Treatment Medication Analysis based on Longitudinal Data with Missing Values using Multiple-Imputation Generalized Estimating Equations. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/94k5p5mx

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):

Yi, Yi. “A Drug-Dependence Treatment Medication Analysis based on Longitudinal Data with Missing Values using Multiple-Imputation Generalized Estimating Equations.” 2014. Thesis, UCLA. Accessed December 08, 2019. http://www.escholarship.org/uc/item/94k5p5mx.

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

MLA Handbook (7th Edition):

Yi, Yi. “A Drug-Dependence Treatment Medication Analysis based on Longitudinal Data with Missing Values using Multiple-Imputation Generalized Estimating Equations.” 2014. Web. 08 Dec 2019.

Vancouver:

Yi Y. A Drug-Dependence Treatment Medication Analysis based on Longitudinal Data with Missing Values using Multiple-Imputation Generalized Estimating Equations. [Internet] [Thesis]. UCLA; 2014. [cited 2019 Dec 08]. Available from: http://www.escholarship.org/uc/item/94k5p5mx.

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

Council of Science Editors:

Yi Y. A Drug-Dependence Treatment Medication Analysis based on Longitudinal Data with Missing Values using Multiple-Imputation Generalized Estimating Equations. [Thesis]. UCLA; 2014. Available from: http://www.escholarship.org/uc/item/94k5p5mx

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


UCLA

5. RIZZO VARELA, SHEMRA. Uncertainty in Meta-Analysis: Bridging the Divide Between Ideal and Available Extracted Data.

Degree: Biostatistics, 2015, UCLA

 Meta-analysis in the health sciences combines evidence from multiple studies to derive stronger conclusions about the efficacy of treatments. In the process of data extraction… (more)

Subjects/Keywords: Biostatistics; Statistics; Bayesian modeling; censoring; imputation; mean difference; missing data; odds ratios

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APA (6th Edition):

RIZZO VARELA, S. (2015). Uncertainty in Meta-Analysis: Bridging the Divide Between Ideal and Available Extracted Data. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/1qg250sq

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):

RIZZO VARELA, SHEMRA. “Uncertainty in Meta-Analysis: Bridging the Divide Between Ideal and Available Extracted Data.” 2015. Thesis, UCLA. Accessed December 08, 2019. http://www.escholarship.org/uc/item/1qg250sq.

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

MLA Handbook (7th Edition):

RIZZO VARELA, SHEMRA. “Uncertainty in Meta-Analysis: Bridging the Divide Between Ideal and Available Extracted Data.” 2015. Web. 08 Dec 2019.

Vancouver:

RIZZO VARELA S. Uncertainty in Meta-Analysis: Bridging the Divide Between Ideal and Available Extracted Data. [Internet] [Thesis]. UCLA; 2015. [cited 2019 Dec 08]. Available from: http://www.escholarship.org/uc/item/1qg250sq.

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

Council of Science Editors:

RIZZO VARELA S. Uncertainty in Meta-Analysis: Bridging the Divide Between Ideal and Available Extracted Data. [Thesis]. UCLA; 2015. Available from: http://www.escholarship.org/uc/item/1qg250sq

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


UCLA

6. Peng, Qin. Trees vs Neurons: Comparison between Denoising Autoencoders and Random Forest for Imputation of Mixed Data from Electronic Medical Records.

Degree: Statistics, 2018, UCLA

 Missing data is a significant challenge impacting almost all studies; however, this is especially true for analyses of electronic health record (EHR). We propose a… (more)

Subjects/Keywords: Statistics; Denoising autoencoder; electronic health records; imputation; mixed-typed data; nonparametric model

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APA (6th Edition):

Peng, Q. (2018). Trees vs Neurons: Comparison between Denoising Autoencoders and Random Forest for Imputation of Mixed Data from Electronic Medical Records. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/4tp3b2bt

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):

Peng, Qin. “Trees vs Neurons: Comparison between Denoising Autoencoders and Random Forest for Imputation of Mixed Data from Electronic Medical Records.” 2018. Thesis, UCLA. Accessed December 08, 2019. http://www.escholarship.org/uc/item/4tp3b2bt.

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

MLA Handbook (7th Edition):

Peng, Qin. “Trees vs Neurons: Comparison between Denoising Autoencoders and Random Forest for Imputation of Mixed Data from Electronic Medical Records.” 2018. Web. 08 Dec 2019.

Vancouver:

Peng Q. Trees vs Neurons: Comparison between Denoising Autoencoders and Random Forest for Imputation of Mixed Data from Electronic Medical Records. [Internet] [Thesis]. UCLA; 2018. [cited 2019 Dec 08]. Available from: http://www.escholarship.org/uc/item/4tp3b2bt.

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

Council of Science Editors:

Peng Q. Trees vs Neurons: Comparison between Denoising Autoencoders and Random Forest for Imputation of Mixed Data from Electronic Medical Records. [Thesis]. UCLA; 2018. Available from: http://www.escholarship.org/uc/item/4tp3b2bt

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


UCLA

7. Suh, Myung-kyung. Dynamic Adaptive Remote Health Monitoring for Patients with Chronic Disease.

Degree: Computer Science, 2012, UCLA

 Chronic diseases are the leading causes of death and disability in the United States. More than 70% of deaths among Americans are caused by chronic… (more)

Subjects/Keywords: Computer science; Medical Data Prediction; Missing Data Imputation; Remote Health Monitoring; Task Optimization; Telemedicine; Wireless Health Monitoring

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APA (6th Edition):

Suh, M. (2012). Dynamic Adaptive Remote Health Monitoring for Patients with Chronic Disease. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/90c96472

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):

Suh, Myung-kyung. “Dynamic Adaptive Remote Health Monitoring for Patients with Chronic Disease.” 2012. Thesis, UCLA. Accessed December 08, 2019. http://www.escholarship.org/uc/item/90c96472.

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

MLA Handbook (7th Edition):

Suh, Myung-kyung. “Dynamic Adaptive Remote Health Monitoring for Patients with Chronic Disease.” 2012. Web. 08 Dec 2019.

Vancouver:

Suh M. Dynamic Adaptive Remote Health Monitoring for Patients with Chronic Disease. [Internet] [Thesis]. UCLA; 2012. [cited 2019 Dec 08]. Available from: http://www.escholarship.org/uc/item/90c96472.

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

Council of Science Editors:

Suh M. Dynamic Adaptive Remote Health Monitoring for Patients with Chronic Disease. [Thesis]. UCLA; 2012. Available from: http://www.escholarship.org/uc/item/90c96472

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


UCLA

8. Majidpour, Mostafa. Time series prediction for Electric Vehicle Charging Load and Solar Power Generation in the context of Smart Grid.

Degree: Electrical Engineering, 2016, UCLA

 In view of the success of machine learning based prediction algorithms in the recent years, in this study, we have employed a selection of these… (more)

Subjects/Keywords: Electrical engineering; Statistics; Artificial intelligence; Electric Vehicles; Forecasting; Imputation; Machine Learning; Smart Grid; Sparse Time Series

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

APA (6th Edition):

Majidpour, M. (2016). Time series prediction for Electric Vehicle Charging Load and Solar Power Generation in the context of Smart Grid. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/5gc4h0wh

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):

Majidpour, Mostafa. “Time series prediction for Electric Vehicle Charging Load and Solar Power Generation in the context of Smart Grid.” 2016. Thesis, UCLA. Accessed December 08, 2019. http://www.escholarship.org/uc/item/5gc4h0wh.

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

MLA Handbook (7th Edition):

Majidpour, Mostafa. “Time series prediction for Electric Vehicle Charging Load and Solar Power Generation in the context of Smart Grid.” 2016. Web. 08 Dec 2019.

Vancouver:

Majidpour M. Time series prediction for Electric Vehicle Charging Load and Solar Power Generation in the context of Smart Grid. [Internet] [Thesis]. UCLA; 2016. [cited 2019 Dec 08]. Available from: http://www.escholarship.org/uc/item/5gc4h0wh.

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

Council of Science Editors:

Majidpour M. Time series prediction for Electric Vehicle Charging Load and Solar Power Generation in the context of Smart Grid. [Thesis]. UCLA; 2016. Available from: http://www.escholarship.org/uc/item/5gc4h0wh

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

9. He, Ren. Multiple Imputation of High-dimensional Mixed Incomplete Data.

Degree: Biostatistics, 2012, UCLA

 It is common in applied research to have large numbers of variables with mixed data types (continuous, binary, ordinal or nomial) measures on a modest… (more)

Subjects/Keywords: Biostatistics; Statistics; factor model; MCMC; Multiple Imputation; PX-MH algorithm

…2.2 Multiple imputation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4… …13 3 Existing multiple imputation approaches for high-dimensional continuous incomplete… …imputation approaches for incomplete data with mixed data types… …5 Newly Proposed Methods of Imputation of High-dimensional Mixed Invi complete Data… …to appear. R. He and T. Belin, Multiple Imputation of High-dimensional Mixed Incomplete… 

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7

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

APA (6th Edition):

He, R. (2012). Multiple Imputation of High-dimensional Mixed Incomplete Data. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/6k30g516

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):

He, Ren. “Multiple Imputation of High-dimensional Mixed Incomplete Data.” 2012. Thesis, UCLA. Accessed December 08, 2019. http://www.escholarship.org/uc/item/6k30g516.

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

MLA Handbook (7th Edition):

He, Ren. “Multiple Imputation of High-dimensional Mixed Incomplete Data.” 2012. Web. 08 Dec 2019.

Vancouver:

He R. Multiple Imputation of High-dimensional Mixed Incomplete Data. [Internet] [Thesis]. UCLA; 2012. [cited 2019 Dec 08]. Available from: http://www.escholarship.org/uc/item/6k30g516.

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

Council of Science Editors:

He R. Multiple Imputation of High-dimensional Mixed Incomplete Data. [Thesis]. UCLA; 2012. Available from: http://www.escholarship.org/uc/item/6k30g516

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

10. Lu, Xiang. Handling Incomplete High-Dimensional Multivariate Longitudinal Data with Mixed Data Types by Multiple Imputation Using a Longitudinal Factor Analysis Model.

Degree: Biostatistics, 2016, UCLA

 We developed an imputation model solving the missing-data problem in a high-dimensional longitudinal data set with mixed data types (continuous and ordinal) based on a… (more)

Subjects/Keywords: Biostatistics; Factor Analysis; High-Dimensional; Imputation; Longitudinal; Missing Data

…5 1.3 Multiple Imputation Based on Longitudinal Factor Analysis and Probit Model… …12 2.3 Multiple Imputation… …13 2.4 Existing Methods Related to Multiple Imputation for High-Dimensional Data with Mixed… …17 2.4.1 Multivariate Normal Imputation… …17 2.4.2 Imputation Based on Mixed-Effect Linear Model ................................. 18… 

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APA (6th Edition):

Lu, X. (2016). Handling Incomplete High-Dimensional Multivariate Longitudinal Data with Mixed Data Types by Multiple Imputation Using a Longitudinal Factor Analysis Model. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/8s57t2gd

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):

Lu, Xiang. “Handling Incomplete High-Dimensional Multivariate Longitudinal Data with Mixed Data Types by Multiple Imputation Using a Longitudinal Factor Analysis Model.” 2016. Thesis, UCLA. Accessed December 08, 2019. http://www.escholarship.org/uc/item/8s57t2gd.

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

MLA Handbook (7th Edition):

Lu, Xiang. “Handling Incomplete High-Dimensional Multivariate Longitudinal Data with Mixed Data Types by Multiple Imputation Using a Longitudinal Factor Analysis Model.” 2016. Web. 08 Dec 2019.

Vancouver:

Lu X. Handling Incomplete High-Dimensional Multivariate Longitudinal Data with Mixed Data Types by Multiple Imputation Using a Longitudinal Factor Analysis Model. [Internet] [Thesis]. UCLA; 2016. [cited 2019 Dec 08]. Available from: http://www.escholarship.org/uc/item/8s57t2gd.

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

Council of Science Editors:

Lu X. Handling Incomplete High-Dimensional Multivariate Longitudinal Data with Mixed Data Types by Multiple Imputation Using a Longitudinal Factor Analysis Model. [Thesis]. UCLA; 2016. Available from: http://www.escholarship.org/uc/item/8s57t2gd

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

.