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You searched for subject:(missing data). Showing records 1 – 30 of 448 total matches.

[1] [2] [3] [4] [5] … [15]

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North Carolina State University

1. Cao, Weihua. Improving Efficiency and Robustness of Doubly Robust Estimators in the Presence of Coarsened Data.

Degree: PhD, Statistics, 2009, North Carolina State University

 Considerable recent interest has focused on doubly robust estimators for a population mean response in the presence of incomplete data, which involve models for both… (more)

Subjects/Keywords: missing data; coarsened data

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

APA (6th Edition):

Cao, W. (2009). Improving Efficiency and Robustness of Doubly Robust Estimators in the Presence of Coarsened Data. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/3774

Chicago Manual of Style (16th Edition):

Cao, Weihua. “Improving Efficiency and Robustness of Doubly Robust Estimators in the Presence of Coarsened Data.” 2009. Doctoral Dissertation, North Carolina State University. Accessed July 09, 2020. http://www.lib.ncsu.edu/resolver/1840.16/3774.

MLA Handbook (7th Edition):

Cao, Weihua. “Improving Efficiency and Robustness of Doubly Robust Estimators in the Presence of Coarsened Data.” 2009. Web. 09 Jul 2020.

Vancouver:

Cao W. Improving Efficiency and Robustness of Doubly Robust Estimators in the Presence of Coarsened Data. [Internet] [Doctoral dissertation]. North Carolina State University; 2009. [cited 2020 Jul 09]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/3774.

Council of Science Editors:

Cao W. Improving Efficiency and Robustness of Doubly Robust Estimators in the Presence of Coarsened Data. [Doctoral Dissertation]. North Carolina State University; 2009. Available from: http://www.lib.ncsu.edu/resolver/1840.16/3774


Vilnius University

2. Utovkaitė, Jurgita. Praleistų duomenų įrašymo metodai baigtinių populiacijų statistikoje.

Degree: Master, 2009, Vilnius University

Netgi tobuliausiai suplanuotame tyrime atsiranda įvairių rūšių klaidų, dėl kurių gali būti gauti nepatikimi ar nepakankamai tikslūs tyrimo rezultatai, taigi labai svarbu kiek įmanoma labiau… (more)

Subjects/Keywords: Įrašymas; Imputation; Missing data

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APA (6th Edition):

Utovkaitė, Jurgita. (2009). Praleistų duomenų įrašymo metodai baigtinių populiacijų statistikoje. (Masters Thesis). Vilnius University. Retrieved from http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2006~D_20081203_184028-21319 ;

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

Utovkaitė, Jurgita. “Praleistų duomenų įrašymo metodai baigtinių populiacijų statistikoje.” 2009. Masters Thesis, Vilnius University. Accessed July 09, 2020. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2006~D_20081203_184028-21319 ;.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

Utovkaitė, Jurgita. “Praleistų duomenų įrašymo metodai baigtinių populiacijų statistikoje.” 2009. Web. 09 Jul 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

Utovkaitė, Jurgita. Praleistų duomenų įrašymo metodai baigtinių populiacijų statistikoje. [Internet] [Masters thesis]. Vilnius University; 2009. [cited 2020 Jul 09]. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2006~D_20081203_184028-21319 ;.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

Utovkaitė, Jurgita. Praleistų duomenų įrašymo metodai baigtinių populiacijų statistikoje. [Masters Thesis]. Vilnius University; 2009. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2006~D_20081203_184028-21319 ;

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


Universiteit Utrecht

3. Wortmann, D.A. Missing Data Techniques in Contract Benchmarking.

Degree: 2016, Universiteit Utrecht

 Organizations may periodically perform benchmarks as a way to measure their performance. This study attemptsto find a method to provide a way of working to… (more)

Subjects/Keywords: missing data; contract benchmarking

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APA (6th Edition):

Wortmann, D. A. (2016). Missing Data Techniques in Contract Benchmarking. (Masters Thesis). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/338673

Chicago Manual of Style (16th Edition):

Wortmann, D A. “Missing Data Techniques in Contract Benchmarking.” 2016. Masters Thesis, Universiteit Utrecht. Accessed July 09, 2020. http://dspace.library.uu.nl:8080/handle/1874/338673.

MLA Handbook (7th Edition):

Wortmann, D A. “Missing Data Techniques in Contract Benchmarking.” 2016. Web. 09 Jul 2020.

Vancouver:

Wortmann DA. Missing Data Techniques in Contract Benchmarking. [Internet] [Masters thesis]. Universiteit Utrecht; 2016. [cited 2020 Jul 09]. Available from: http://dspace.library.uu.nl:8080/handle/1874/338673.

Council of Science Editors:

Wortmann DA. Missing Data Techniques in Contract Benchmarking. [Masters Thesis]. Universiteit Utrecht; 2016. Available from: http://dspace.library.uu.nl:8080/handle/1874/338673


University of Waterloo

4. Ahmed, Muhamad Rashid. An Investigation of Methods for Missing Data in Hierarchical Models for Discrete Data.

Degree: 2011, University of Waterloo

 Hierarchical models are applicable to modeling data from complex surveys or longitudinal data when a clustered or multistage sample design is employed. The focus of… (more)

Subjects/Keywords: Missing Data; multilevel Model

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APA (6th Edition):

Ahmed, M. R. (2011). An Investigation of Methods for Missing Data in Hierarchical Models for Discrete Data. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/5813

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):

Ahmed, Muhamad Rashid. “An Investigation of Methods for Missing Data in Hierarchical Models for Discrete Data.” 2011. Thesis, University of Waterloo. Accessed July 09, 2020. http://hdl.handle.net/10012/5813.

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

MLA Handbook (7th Edition):

Ahmed, Muhamad Rashid. “An Investigation of Methods for Missing Data in Hierarchical Models for Discrete Data.” 2011. Web. 09 Jul 2020.

Vancouver:

Ahmed MR. An Investigation of Methods for Missing Data in Hierarchical Models for Discrete Data. [Internet] [Thesis]. University of Waterloo; 2011. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/10012/5813.

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

Council of Science Editors:

Ahmed MR. An Investigation of Methods for Missing Data in Hierarchical Models for Discrete Data. [Thesis]. University of Waterloo; 2011. Available from: http://hdl.handle.net/10012/5813

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


University of Notre Dame

5. Qian Zhang. Methods for Moderation Analysis with Missing Data</h1>.

Degree: Psychology, 2014, University of Notre Dame

  In the study, I consider a simple moderated multiple regression (MMR) model, where the effect of predictor X on the outcome Y is moderated… (more)

Subjects/Keywords: moderated multiple regression; missing data

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APA (6th Edition):

Zhang, Q. (2014). Methods for Moderation Analysis with Missing Data</h1>. (Thesis). University of Notre Dame. Retrieved from https://curate.nd.edu/show/bk128912m57

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):

Zhang, Qian. “Methods for Moderation Analysis with Missing Data</h1>.” 2014. Thesis, University of Notre Dame. Accessed July 09, 2020. https://curate.nd.edu/show/bk128912m57.

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

MLA Handbook (7th Edition):

Zhang, Qian. “Methods for Moderation Analysis with Missing Data</h1>.” 2014. Web. 09 Jul 2020.

Vancouver:

Zhang Q. Methods for Moderation Analysis with Missing Data</h1>. [Internet] [Thesis]. University of Notre Dame; 2014. [cited 2020 Jul 09]. Available from: https://curate.nd.edu/show/bk128912m57.

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

Council of Science Editors:

Zhang Q. Methods for Moderation Analysis with Missing Data</h1>. [Thesis]. University of Notre Dame; 2014. Available from: https://curate.nd.edu/show/bk128912m57

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


Victoria University of Wellington

6. Luo, Maoxin. Imputation on the Food, Nutrition and Environment Surveys 2007 and 2009 data.

Degree: 2013, Victoria University of Wellington

 The Food Nutrition Environment Survey (FNES) is a survey of New Zealand early childhood centres and schools and the food and nutritional services that they… (more)

Subjects/Keywords: Multiple imputation; Bayesian; Missing data

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APA (6th Edition):

Luo, M. (2013). Imputation on the Food, Nutrition and Environment Surveys 2007 and 2009 data. (Masters Thesis). Victoria University of Wellington. Retrieved from http://hdl.handle.net/10063/2796

Chicago Manual of Style (16th Edition):

Luo, Maoxin. “Imputation on the Food, Nutrition and Environment Surveys 2007 and 2009 data.” 2013. Masters Thesis, Victoria University of Wellington. Accessed July 09, 2020. http://hdl.handle.net/10063/2796.

MLA Handbook (7th Edition):

Luo, Maoxin. “Imputation on the Food, Nutrition and Environment Surveys 2007 and 2009 data.” 2013. Web. 09 Jul 2020.

Vancouver:

Luo M. Imputation on the Food, Nutrition and Environment Surveys 2007 and 2009 data. [Internet] [Masters thesis]. Victoria University of Wellington; 2013. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/10063/2796.

Council of Science Editors:

Luo M. Imputation on the Food, Nutrition and Environment Surveys 2007 and 2009 data. [Masters Thesis]. Victoria University of Wellington; 2013. Available from: http://hdl.handle.net/10063/2796


University of North Texas

7. St. Clair, Suzanne W. Missing Data Treatments at the Second Level of Hierarchical Linear Models.

Degree: 2011, University of North Texas

 The current study evaluated the performance of traditional versus modern MDTs in the estimation of fixed-effects and variance components for data missing at the second… (more)

Subjects/Keywords: hierarchical linear models; missing data treatments; missing data

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APA (6th Edition):

St. Clair, S. W. (2011). Missing Data Treatments at the Second Level of Hierarchical Linear Models. (Thesis). University of North Texas. Retrieved from https://digital.library.unt.edu/ark:/67531/metadc84282/

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):

St. Clair, Suzanne W. “Missing Data Treatments at the Second Level of Hierarchical Linear Models.” 2011. Thesis, University of North Texas. Accessed July 09, 2020. https://digital.library.unt.edu/ark:/67531/metadc84282/.

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

MLA Handbook (7th Edition):

St. Clair, Suzanne W. “Missing Data Treatments at the Second Level of Hierarchical Linear Models.” 2011. Web. 09 Jul 2020.

Vancouver:

St. Clair SW. Missing Data Treatments at the Second Level of Hierarchical Linear Models. [Internet] [Thesis]. University of North Texas; 2011. [cited 2020 Jul 09]. Available from: https://digital.library.unt.edu/ark:/67531/metadc84282/.

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

Council of Science Editors:

St. Clair SW. Missing Data Treatments at the Second Level of Hierarchical Linear Models. [Thesis]. University of North Texas; 2011. Available from: https://digital.library.unt.edu/ark:/67531/metadc84282/

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


Penn State University

8. Karwa, Vishesh. Likelihood based inference in data privacy and other discrete missing data problems.

Degree: PhD, Statistics, 2014, Penn State University

 In this dissertation, we develop procedures for performing likelihood based inference in discrete data problems in the areas of data privacy, causal inference and ecological… (more)

Subjects/Keywords: Missing Data; Likelihood; Privacy; networks; discrete data

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

APA (6th Edition):

Karwa, V. (2014). Likelihood based inference in data privacy and other discrete missing data problems. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/22702

Chicago Manual of Style (16th Edition):

Karwa, Vishesh. “Likelihood based inference in data privacy and other discrete missing data problems.” 2014. Doctoral Dissertation, Penn State University. Accessed July 09, 2020. https://etda.libraries.psu.edu/catalog/22702.

MLA Handbook (7th Edition):

Karwa, Vishesh. “Likelihood based inference in data privacy and other discrete missing data problems.” 2014. Web. 09 Jul 2020.

Vancouver:

Karwa V. Likelihood based inference in data privacy and other discrete missing data problems. [Internet] [Doctoral dissertation]. Penn State University; 2014. [cited 2020 Jul 09]. Available from: https://etda.libraries.psu.edu/catalog/22702.

Council of Science Editors:

Karwa V. Likelihood based inference in data privacy and other discrete missing data problems. [Doctoral Dissertation]. Penn State University; 2014. Available from: https://etda.libraries.psu.edu/catalog/22702


Cornell University

9. Steingrimsson, Jon. Information Recovery With Missing Data When Outcomes Are Right Censored.

Degree: 2015, Cornell University

 This dissertation focuses on utilizing information more efficiently in several settings when some observations are right-censored using the semiparametric efficiency theory developed in Robins et… (more)

Subjects/Keywords: Missing Data; Semiparametric Theory; Censored Data

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APA (6th Edition):

Steingrimsson, J. (2015). Information Recovery With Missing Data When Outcomes Are Right Censored. (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/41100

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):

Steingrimsson, Jon. “Information Recovery With Missing Data When Outcomes Are Right Censored. ” 2015. Thesis, Cornell University. Accessed July 09, 2020. http://hdl.handle.net/1813/41100.

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

MLA Handbook (7th Edition):

Steingrimsson, Jon. “Information Recovery With Missing Data When Outcomes Are Right Censored. ” 2015. Web. 09 Jul 2020.

Vancouver:

Steingrimsson J. Information Recovery With Missing Data When Outcomes Are Right Censored. [Internet] [Thesis]. Cornell University; 2015. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/1813/41100.

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

Council of Science Editors:

Steingrimsson J. Information Recovery With Missing Data When Outcomes Are Right Censored. [Thesis]. Cornell University; 2015. Available from: http://hdl.handle.net/1813/41100

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


University of Illinois – Chicago

10. Swanlund, Andrew Peter. Correcting for Rater Bias in the Presence of Non-Ignorable Missing Ratings.

Degree: 2016, University of Illinois – Chicago

 This thesis addresses the problem of non-ignorable missing ratings in judge rated data. A Bayesian bivariate probit ordinal missing data model implemented with Markov chain… (more)

Subjects/Keywords: Psychometrics; Judge-Rated Data; Missing Data Analysis

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APA (6th Edition):

Swanlund, A. P. (2016). Correcting for Rater Bias in the Presence of Non-Ignorable Missing Ratings. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/21553

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):

Swanlund, Andrew Peter. “Correcting for Rater Bias in the Presence of Non-Ignorable Missing Ratings.” 2016. Thesis, University of Illinois – Chicago. Accessed July 09, 2020. http://hdl.handle.net/10027/21553.

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

MLA Handbook (7th Edition):

Swanlund, Andrew Peter. “Correcting for Rater Bias in the Presence of Non-Ignorable Missing Ratings.” 2016. Web. 09 Jul 2020.

Vancouver:

Swanlund AP. Correcting for Rater Bias in the Presence of Non-Ignorable Missing Ratings. [Internet] [Thesis]. University of Illinois – Chicago; 2016. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/10027/21553.

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

Council of Science Editors:

Swanlund AP. Correcting for Rater Bias in the Presence of Non-Ignorable Missing Ratings. [Thesis]. University of Illinois – Chicago; 2016. Available from: http://hdl.handle.net/10027/21553

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


Florida International University

11. Che, Suisui. Study on a Hierarchy Model.

Degree: MS, Statistics, 2012, Florida International University

  The statistical inferences about the parameters of Binomial-Poisson hierarchy model are discussed. Based on the estimators of paired observations we consider the other two… (more)

Subjects/Keywords: Binomial-Poisson distribution; unpaired data; missing data

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APA (6th Edition):

Che, S. (2012). Study on a Hierarchy Model. (Thesis). Florida International University. Retrieved from https://digitalcommons.fiu.edu/etd/611 ; 10.25148/etd.FI12052102 ; FI12052102

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):

Che, Suisui. “Study on a Hierarchy Model.” 2012. Thesis, Florida International University. Accessed July 09, 2020. https://digitalcommons.fiu.edu/etd/611 ; 10.25148/etd.FI12052102 ; FI12052102.

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

MLA Handbook (7th Edition):

Che, Suisui. “Study on a Hierarchy Model.” 2012. Web. 09 Jul 2020.

Vancouver:

Che S. Study on a Hierarchy Model. [Internet] [Thesis]. Florida International University; 2012. [cited 2020 Jul 09]. Available from: https://digitalcommons.fiu.edu/etd/611 ; 10.25148/etd.FI12052102 ; FI12052102.

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

Council of Science Editors:

Che S. Study on a Hierarchy Model. [Thesis]. Florida International University; 2012. Available from: https://digitalcommons.fiu.edu/etd/611 ; 10.25148/etd.FI12052102 ; FI12052102

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


University of Akron

12. Medvedeff, Alexander Mark. On the Interpolation of Missing Dependent Variable Observations.

Degree: MA, Economics, 2008, University of Akron

 This paper utilizes a Monte Carlo experiment to simulate random missing observations in a dataset in order to analyze the effects of how various techniques… (more)

Subjects/Keywords: Economics; Statistics; Interpolation; Missing Data; Missing Observations; Econometrics; Monte Carlo

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APA (6th Edition):

Medvedeff, A. M. (2008). On the Interpolation of Missing Dependent Variable Observations. (Masters Thesis). University of Akron. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=akron1208185971

Chicago Manual of Style (16th Edition):

Medvedeff, Alexander Mark. “On the Interpolation of Missing Dependent Variable Observations.” 2008. Masters Thesis, University of Akron. Accessed July 09, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=akron1208185971.

MLA Handbook (7th Edition):

Medvedeff, Alexander Mark. “On the Interpolation of Missing Dependent Variable Observations.” 2008. Web. 09 Jul 2020.

Vancouver:

Medvedeff AM. On the Interpolation of Missing Dependent Variable Observations. [Internet] [Masters thesis]. University of Akron; 2008. [cited 2020 Jul 09]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1208185971.

Council of Science Editors:

Medvedeff AM. On the Interpolation of Missing Dependent Variable Observations. [Masters Thesis]. University of Akron; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1208185971


Oregon State University

13. Lu, Lin. Unconditional estimating equation approaches for missing data.

Degree: PhD, Statistics, 2007, Oregon State University

Missing data can lead to biased and inefficient estimation if the missing mechanism is not taken into account in the analysis. In this dissertation we… (more)

Subjects/Keywords: missing data; Missing observations (Statistics)

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APA (6th Edition):

Lu, L. (2007). Unconditional estimating equation approaches for missing data. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/7537

Chicago Manual of Style (16th Edition):

Lu, Lin. “Unconditional estimating equation approaches for missing data.” 2007. Doctoral Dissertation, Oregon State University. Accessed July 09, 2020. http://hdl.handle.net/1957/7537.

MLA Handbook (7th Edition):

Lu, Lin. “Unconditional estimating equation approaches for missing data.” 2007. Web. 09 Jul 2020.

Vancouver:

Lu L. Unconditional estimating equation approaches for missing data. [Internet] [Doctoral dissertation]. Oregon State University; 2007. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/1957/7537.

Council of Science Editors:

Lu L. Unconditional estimating equation approaches for missing data. [Doctoral Dissertation]. Oregon State University; 2007. Available from: http://hdl.handle.net/1957/7537


The Ohio State University

14. Kohlschmidt, Jessica Kay. RANKED SET SAMPLING: A LOOK AT ALLOCATION ISSUES AND MISSING DATA COMPLICATIONS.

Degree: PhD, Statistics, 2009, The Ohio State University

  Ranked set sampling (RSS) is an alternative to simple random sampling that has been shown to outperform simple random sampling (SRS) in many situations.… (more)

Subjects/Keywords: Statistics; Ranked Set Sampling (RSS); Missing Data

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APA (6th Edition):

Kohlschmidt, J. K. (2009). RANKED SET SAMPLING: A LOOK AT ALLOCATION ISSUES AND MISSING DATA COMPLICATIONS. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1236779896

Chicago Manual of Style (16th Edition):

Kohlschmidt, Jessica Kay. “RANKED SET SAMPLING: A LOOK AT ALLOCATION ISSUES AND MISSING DATA COMPLICATIONS.” 2009. Doctoral Dissertation, The Ohio State University. Accessed July 09, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1236779896.

MLA Handbook (7th Edition):

Kohlschmidt, Jessica Kay. “RANKED SET SAMPLING: A LOOK AT ALLOCATION ISSUES AND MISSING DATA COMPLICATIONS.” 2009. Web. 09 Jul 2020.

Vancouver:

Kohlschmidt JK. RANKED SET SAMPLING: A LOOK AT ALLOCATION ISSUES AND MISSING DATA COMPLICATIONS. [Internet] [Doctoral dissertation]. The Ohio State University; 2009. [cited 2020 Jul 09]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1236779896.

Council of Science Editors:

Kohlschmidt JK. RANKED SET SAMPLING: A LOOK AT ALLOCATION ISSUES AND MISSING DATA COMPLICATIONS. [Doctoral Dissertation]. The Ohio State University; 2009. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1236779896


Boston University

15. Baltrusaitis, Kristin. Comparative evaluation of methods that adjust for reporting biases in participatory surveillance systems.

Degree: PhD, Biostatistics, 2019, Boston University

 Over the past decade the widespread proliferation of mobile devices and wearable technology has significantly changed the landscape of epidemiological data gathering and evolved into… (more)

Subjects/Keywords: Biostatistics; Digital epidemiology; Influenza; Missing data; Surveillance

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APA (6th Edition):

Baltrusaitis, K. (2019). Comparative evaluation of methods that adjust for reporting biases in participatory surveillance systems. (Doctoral Dissertation). Boston University. Retrieved from http://hdl.handle.net/2144/38799

Chicago Manual of Style (16th Edition):

Baltrusaitis, Kristin. “Comparative evaluation of methods that adjust for reporting biases in participatory surveillance systems.” 2019. Doctoral Dissertation, Boston University. Accessed July 09, 2020. http://hdl.handle.net/2144/38799.

MLA Handbook (7th Edition):

Baltrusaitis, Kristin. “Comparative evaluation of methods that adjust for reporting biases in participatory surveillance systems.” 2019. Web. 09 Jul 2020.

Vancouver:

Baltrusaitis K. Comparative evaluation of methods that adjust for reporting biases in participatory surveillance systems. [Internet] [Doctoral dissertation]. Boston University; 2019. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/2144/38799.

Council of Science Editors:

Baltrusaitis K. Comparative evaluation of methods that adjust for reporting biases in participatory surveillance systems. [Doctoral Dissertation]. Boston University; 2019. Available from: http://hdl.handle.net/2144/38799


University of Toronto

16. Rudra, Malvika. Application of Imputation Methods in the Analysis of Freight Trip Generation in the Greater Toronto and Hamilton Area.

Degree: 2014, University of Toronto

Missing data is a common issue in empirical research, especially in complex surveys involving a large number of respondents. In 2012-13, a shipper-based, establishment survey… (more)

Subjects/Keywords: freight trip generation; imputation; missing data; 0543

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APA (6th Edition):

Rudra, M. (2014). Application of Imputation Methods in the Analysis of Freight Trip Generation in the Greater Toronto and Hamilton Area. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/68004

Chicago Manual of Style (16th Edition):

Rudra, Malvika. “Application of Imputation Methods in the Analysis of Freight Trip Generation in the Greater Toronto and Hamilton Area.” 2014. Masters Thesis, University of Toronto. Accessed July 09, 2020. http://hdl.handle.net/1807/68004.

MLA Handbook (7th Edition):

Rudra, Malvika. “Application of Imputation Methods in the Analysis of Freight Trip Generation in the Greater Toronto and Hamilton Area.” 2014. Web. 09 Jul 2020.

Vancouver:

Rudra M. Application of Imputation Methods in the Analysis of Freight Trip Generation in the Greater Toronto and Hamilton Area. [Internet] [Masters thesis]. University of Toronto; 2014. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/1807/68004.

Council of Science Editors:

Rudra M. Application of Imputation Methods in the Analysis of Freight Trip Generation in the Greater Toronto and Hamilton Area. [Masters Thesis]. University of Toronto; 2014. Available from: http://hdl.handle.net/1807/68004


University of Edinburgh

17. Read, Stephanie Helen. Applying missing data methods to routine data using the example of a population-based register of patients with diabetes.

Degree: PhD, 2015, University of Edinburgh

 Background: Routinely-collected data offer great potential for epidemiological research and could be used to make randomised controlled trials (RCTs) more efficient. The use of routine… (more)

Subjects/Keywords: 616.4; missing data; diabetes; obesity; mortality

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

APA (6th Edition):

Read, S. H. (2015). Applying missing data methods to routine data using the example of a population-based register of patients with diabetes. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/21078

Chicago Manual of Style (16th Edition):

Read, Stephanie Helen. “Applying missing data methods to routine data using the example of a population-based register of patients with diabetes.” 2015. Doctoral Dissertation, University of Edinburgh. Accessed July 09, 2020. http://hdl.handle.net/1842/21078.

MLA Handbook (7th Edition):

Read, Stephanie Helen. “Applying missing data methods to routine data using the example of a population-based register of patients with diabetes.” 2015. Web. 09 Jul 2020.

Vancouver:

Read SH. Applying missing data methods to routine data using the example of a population-based register of patients with diabetes. [Internet] [Doctoral dissertation]. University of Edinburgh; 2015. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/1842/21078.

Council of Science Editors:

Read SH. Applying missing data methods to routine data using the example of a population-based register of patients with diabetes. [Doctoral Dissertation]. University of Edinburgh; 2015. Available from: http://hdl.handle.net/1842/21078


University of Edinburgh

18. Holm Hansen, Christian. Analysis of routinely collected repeated patient outcomes.

Degree: PhD, 2014, University of Edinburgh

 Clinical practice should be based on the best available evidence. Ideally such evidence is obtained through rigorously conducted, purpose-designed clinical studies such as randomised controlled… (more)

Subjects/Keywords: 610.72; medical statistics; missing data; longitudinal analysis

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APA (6th Edition):

Holm Hansen, C. (2014). Analysis of routinely collected repeated patient outcomes. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/9556

Chicago Manual of Style (16th Edition):

Holm Hansen, Christian. “Analysis of routinely collected repeated patient outcomes.” 2014. Doctoral Dissertation, University of Edinburgh. Accessed July 09, 2020. http://hdl.handle.net/1842/9556.

MLA Handbook (7th Edition):

Holm Hansen, Christian. “Analysis of routinely collected repeated patient outcomes.” 2014. Web. 09 Jul 2020.

Vancouver:

Holm Hansen C. Analysis of routinely collected repeated patient outcomes. [Internet] [Doctoral dissertation]. University of Edinburgh; 2014. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/1842/9556.

Council of Science Editors:

Holm Hansen C. Analysis of routinely collected repeated patient outcomes. [Doctoral Dissertation]. University of Edinburgh; 2014. Available from: http://hdl.handle.net/1842/9556


University of Limerick

19. Berkery, Elaine M. Missing data analysis with the Mahalanobis distance.

Degree: 2016, University of Limerick

Missing data occur regularly when data are collected for a variety of reasons such as participants refusing to answer question in surveys or machines failing… (more)

Subjects/Keywords: mathematics; Mahalanobis distance; missing data analysis

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

APA (6th Edition):

Berkery, E. M. (2016). Missing data analysis with the Mahalanobis distance. (Thesis). University of Limerick. Retrieved from http://hdl.handle.net/10344/5235

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):

Berkery, Elaine M. “Missing data analysis with the Mahalanobis distance.” 2016. Thesis, University of Limerick. Accessed July 09, 2020. http://hdl.handle.net/10344/5235.

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

MLA Handbook (7th Edition):

Berkery, Elaine M. “Missing data analysis with the Mahalanobis distance.” 2016. Web. 09 Jul 2020.

Vancouver:

Berkery EM. Missing data analysis with the Mahalanobis distance. [Internet] [Thesis]. University of Limerick; 2016. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/10344/5235.

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

Council of Science Editors:

Berkery EM. Missing data analysis with the Mahalanobis distance. [Thesis]. University of Limerick; 2016. Available from: http://hdl.handle.net/10344/5235

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


Virginia Commonwealth University

20. Morrissett, Marion. Missing Data in the Relational Model.

Degree: PhD, Engineering, 2013, Virginia Commonwealth University

 This research provides improved support for missing data in the relational model and relational database systems. There is a need for a systematic method to… (more)

Subjects/Keywords: relational database; missing data; incomplete information; Engineering

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APA (6th Edition):

Morrissett, M. (2013). Missing Data in the Relational Model. (Doctoral Dissertation). Virginia Commonwealth University. Retrieved from https://doi.org/10.25772/3BBD-CZ71 ; https://scholarscompass.vcu.edu/etd/3004

Chicago Manual of Style (16th Edition):

Morrissett, Marion. “Missing Data in the Relational Model.” 2013. Doctoral Dissertation, Virginia Commonwealth University. Accessed July 09, 2020. https://doi.org/10.25772/3BBD-CZ71 ; https://scholarscompass.vcu.edu/etd/3004.

MLA Handbook (7th Edition):

Morrissett, Marion. “Missing Data in the Relational Model.” 2013. Web. 09 Jul 2020.

Vancouver:

Morrissett M. Missing Data in the Relational Model. [Internet] [Doctoral dissertation]. Virginia Commonwealth University; 2013. [cited 2020 Jul 09]. Available from: https://doi.org/10.25772/3BBD-CZ71 ; https://scholarscompass.vcu.edu/etd/3004.

Council of Science Editors:

Morrissett M. Missing Data in the Relational Model. [Doctoral Dissertation]. Virginia Commonwealth University; 2013. Available from: https://doi.org/10.25772/3BBD-CZ71 ; https://scholarscompass.vcu.edu/etd/3004


Virginia Tech

21. Zaghlool, Shaza B. Dynamic Causal Modeling Across Network Topologies.

Degree: PhD, Computer Engineering, 2014, Virginia Tech

 Dynamic Causal Modeling (DCM) uses dynamical systems to represent the high-level neural processing strategy for a given cognitive task. The logical network topology of the… (more)

Subjects/Keywords: Dynamic Causal Modeling; Expectation-Maximization; Missing Data

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APA (6th Edition):

Zaghlool, S. B. (2014). Dynamic Causal Modeling Across Network Topologies. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/46874

Chicago Manual of Style (16th Edition):

Zaghlool, Shaza B. “Dynamic Causal Modeling Across Network Topologies.” 2014. Doctoral Dissertation, Virginia Tech. Accessed July 09, 2020. http://hdl.handle.net/10919/46874.

MLA Handbook (7th Edition):

Zaghlool, Shaza B. “Dynamic Causal Modeling Across Network Topologies.” 2014. Web. 09 Jul 2020.

Vancouver:

Zaghlool SB. Dynamic Causal Modeling Across Network Topologies. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/10919/46874.

Council of Science Editors:

Zaghlool SB. Dynamic Causal Modeling Across Network Topologies. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/46874


University of Rochester

22. Majumder, Madhurima. Conditional Tests for Multivariate One-sided Hypotheses with Missing Data.

Degree: PhD, 2020, University of Rochester

 Treatment comparisons in randomized clinical trials usually involve several outcomes. Sometimes it is of interest to determine whether there is a treatment-associated improvement in disease… (more)

Subjects/Keywords: Hypothesis testing; Missing data; Order-restricted interference

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APA (6th Edition):

Majumder, M. (2020). Conditional Tests for Multivariate One-sided Hypotheses with Missing Data. (Doctoral Dissertation). University of Rochester. Retrieved from http://hdl.handle.net/1802/35508

Chicago Manual of Style (16th Edition):

Majumder, Madhurima. “Conditional Tests for Multivariate One-sided Hypotheses with Missing Data.” 2020. Doctoral Dissertation, University of Rochester. Accessed July 09, 2020. http://hdl.handle.net/1802/35508.

MLA Handbook (7th Edition):

Majumder, Madhurima. “Conditional Tests for Multivariate One-sided Hypotheses with Missing Data.” 2020. Web. 09 Jul 2020.

Vancouver:

Majumder M. Conditional Tests for Multivariate One-sided Hypotheses with Missing Data. [Internet] [Doctoral dissertation]. University of Rochester; 2020. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/1802/35508.

Council of Science Editors:

Majumder M. Conditional Tests for Multivariate One-sided Hypotheses with Missing Data. [Doctoral Dissertation]. University of Rochester; 2020. Available from: http://hdl.handle.net/1802/35508


Ohio University

23. Parsons, Michael M. Planned Missing Data Designs in Communication Research.

Degree: PhD, Communication Studies (Communication), 2013, Ohio University

 Prominent among the many methodological challenges communication research faces are the relative lack of longitudinal research conducted in the discipline and the threats to validity… (more)

Subjects/Keywords: Communication; missing data; planned missing data; longitudinal; multiple imputation; communication; communication research

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APA (6th Edition):

Parsons, M. M. (2013). Planned Missing Data Designs in Communication Research. (Doctoral Dissertation). Ohio University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1376579676

Chicago Manual of Style (16th Edition):

Parsons, Michael M. “Planned Missing Data Designs in Communication Research.” 2013. Doctoral Dissertation, Ohio University. Accessed July 09, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1376579676.

MLA Handbook (7th Edition):

Parsons, Michael M. “Planned Missing Data Designs in Communication Research.” 2013. Web. 09 Jul 2020.

Vancouver:

Parsons MM. Planned Missing Data Designs in Communication Research. [Internet] [Doctoral dissertation]. Ohio University; 2013. [cited 2020 Jul 09]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1376579676.

Council of Science Editors:

Parsons MM. Planned Missing Data Designs in Communication Research. [Doctoral Dissertation]. Ohio University; 2013. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1376579676


Uppsala University

24. Huo, Zhao. A Comparsion of Multiple Imputation Methods for Missing Covariate Values in Recurrent Event Data.

Degree: Statistics, 2015, Uppsala University

  Multiple imputation (MI) is a commonly used approach to impute missing data. This thesis studies missing covariates in recurrent event data, and discusses ways… (more)

Subjects/Keywords: Missing data; Multiple imputation; Missing covariates; Recurrent event data; Cox PH model; PWP model

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

APA (6th Edition):

Huo, Z. (2015). A Comparsion of Multiple Imputation Methods for Missing Covariate Values in Recurrent Event Data. (Thesis). Uppsala University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-256602

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):

Huo, Zhao. “A Comparsion of Multiple Imputation Methods for Missing Covariate Values in Recurrent Event Data.” 2015. Thesis, Uppsala University. Accessed July 09, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-256602.

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

MLA Handbook (7th Edition):

Huo, Zhao. “A Comparsion of Multiple Imputation Methods for Missing Covariate Values in Recurrent Event Data.” 2015. Web. 09 Jul 2020.

Vancouver:

Huo Z. A Comparsion of Multiple Imputation Methods for Missing Covariate Values in Recurrent Event Data. [Internet] [Thesis]. Uppsala University; 2015. [cited 2020 Jul 09]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-256602.

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

Council of Science Editors:

Huo Z. A Comparsion of Multiple Imputation Methods for Missing Covariate Values in Recurrent Event Data. [Thesis]. Uppsala University; 2015. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-256602

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


University of Texas – Austin

25. Feng, Qian, Ph. D. Essays on Causal Inference with Endogeneity and Missing Data.

Degree: PhD, Economics, 2018, University of Texas – Austin

 This dissertation strives to devise novel yet easy-to-implement estima- tion and inference procedures for economists to solve complicated real world problems. It provides by far… (more)

Subjects/Keywords: Causal inference; Endogeneity; Missing data; Missing instruments; Instrumental variables (IV) estimation; Heterogeneity; Treatment effects

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

APA (6th Edition):

Feng, Qian, P. D. (2018). Essays on Causal Inference with Endogeneity and Missing Data. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63356

Chicago Manual of Style (16th Edition):

Feng, Qian, Ph D. “Essays on Causal Inference with Endogeneity and Missing Data.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed July 09, 2020. http://hdl.handle.net/2152/63356.

MLA Handbook (7th Edition):

Feng, Qian, Ph D. “Essays on Causal Inference with Endogeneity and Missing Data.” 2018. Web. 09 Jul 2020.

Vancouver:

Feng, Qian PD. Essays on Causal Inference with Endogeneity and Missing Data. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/2152/63356.

Council of Science Editors:

Feng, Qian PD. Essays on Causal Inference with Endogeneity and Missing Data. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/63356


George Mason University

26. Cheema, Jehanzeb. Handling Missing Data in Educational Research Using SPSS .

Degree: 2012, George Mason University

 This study looked at the effect of a number of factors such as the choice of analytical method, the handling method for missing data, sample… (more)

Subjects/Keywords: Imputation Method; Item Non-Response; Listwise Deletion; Missing Data; Multiple Imputation; Missing Value

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

APA (6th Edition):

Cheema, J. (2012). Handling Missing Data in Educational Research Using SPSS . (Thesis). George Mason University. Retrieved from http://hdl.handle.net/1920/7840

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):

Cheema, Jehanzeb. “Handling Missing Data in Educational Research Using SPSS .” 2012. Thesis, George Mason University. Accessed July 09, 2020. http://hdl.handle.net/1920/7840.

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

MLA Handbook (7th Edition):

Cheema, Jehanzeb. “Handling Missing Data in Educational Research Using SPSS .” 2012. Web. 09 Jul 2020.

Vancouver:

Cheema J. Handling Missing Data in Educational Research Using SPSS . [Internet] [Thesis]. George Mason University; 2012. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/1920/7840.

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

Council of Science Editors:

Cheema J. Handling Missing Data in Educational Research Using SPSS . [Thesis]. George Mason University; 2012. Available from: http://hdl.handle.net/1920/7840

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


University of Arizona

27. Jia, Ziyue. A Nonparametric Multiple Imputation Approach For MNAR Mechanism Using the Sample Selection Model Framework .

Degree: 2019, University of Arizona

Missing data is an unavoidable issue when performing data analysis. If the missing probability is related to unobserved variables, missingness is considered as missing not… (more)

Subjects/Keywords: Missing data; Missing not at random (MNAR); Model misspecification; Sample selection model

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

APA (6th Edition):

Jia, Z. (2019). A Nonparametric Multiple Imputation Approach For MNAR Mechanism Using the Sample Selection Model Framework . (Masters Thesis). University of Arizona. Retrieved from http://hdl.handle.net/10150/632554

Chicago Manual of Style (16th Edition):

Jia, Ziyue. “A Nonparametric Multiple Imputation Approach For MNAR Mechanism Using the Sample Selection Model Framework .” 2019. Masters Thesis, University of Arizona. Accessed July 09, 2020. http://hdl.handle.net/10150/632554.

MLA Handbook (7th Edition):

Jia, Ziyue. “A Nonparametric Multiple Imputation Approach For MNAR Mechanism Using the Sample Selection Model Framework .” 2019. Web. 09 Jul 2020.

Vancouver:

Jia Z. A Nonparametric Multiple Imputation Approach For MNAR Mechanism Using the Sample Selection Model Framework . [Internet] [Masters thesis]. University of Arizona; 2019. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/10150/632554.

Council of Science Editors:

Jia Z. A Nonparametric Multiple Imputation Approach For MNAR Mechanism Using the Sample Selection Model Framework . [Masters Thesis]. University of Arizona; 2019. Available from: http://hdl.handle.net/10150/632554


University of Florida

28. Zhang,Juheng. Linear Discrimination with Strategically Missing Values.

Degree: PhD, Business Administration - Information Systems and Operations Management, 2011, University of Florida

 This study analyzes a problem where a decision maker needs to estimate missing values that are hidden strategically by agents so that further analysis can… (more)

Subjects/Keywords: Anticipation; Data imputation; Datasets; Estimation methods; Hyperplanes; Mathematical vectors; Missing data; Statistics; Test ranges; Vertices; classification  – data  – linear  – missing  – strategic  – support

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

APA (6th Edition):

Zhang,Juheng. (2011). Linear Discrimination with Strategically Missing Values. (Doctoral Dissertation). University of Florida. Retrieved from https://ufdc.ufl.edu/UFE0043287

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

Zhang,Juheng. “Linear Discrimination with Strategically Missing Values.” 2011. Doctoral Dissertation, University of Florida. Accessed July 09, 2020. https://ufdc.ufl.edu/UFE0043287.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

Zhang,Juheng. “Linear Discrimination with Strategically Missing Values.” 2011. Web. 09 Jul 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

Zhang,Juheng. Linear Discrimination with Strategically Missing Values. [Internet] [Doctoral dissertation]. University of Florida; 2011. [cited 2020 Jul 09]. Available from: https://ufdc.ufl.edu/UFE0043287.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

Zhang,Juheng. Linear Discrimination with Strategically Missing Values. [Doctoral Dissertation]. University of Florida; 2011. Available from: https://ufdc.ufl.edu/UFE0043287

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of KwaZulu-Natal

29. Ndlela, Thamsanqa Innocent. Bayesian data augmentation using MCMC: application to missing values imputation on cancer medication data.

Degree: 2017, University of KwaZulu-Natal

Missing data is a very serious issue that negatively affect inferences and findings of researchers in data science and statistics. The ignorance of missing data(more)

Subjects/Keywords: Cancer.; EM Algorithm.; Data augmentation.; Bayesian approach.; Missing data.

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

APA (6th Edition):

Ndlela, T. I. (2017). Bayesian data augmentation using MCMC: application to missing values imputation on cancer medication data. (Thesis). University of KwaZulu-Natal. Retrieved from http://hdl.handle.net/10413/15641

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):

Ndlela, Thamsanqa Innocent. “Bayesian data augmentation using MCMC: application to missing values imputation on cancer medication data.” 2017. Thesis, University of KwaZulu-Natal. Accessed July 09, 2020. http://hdl.handle.net/10413/15641.

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

MLA Handbook (7th Edition):

Ndlela, Thamsanqa Innocent. “Bayesian data augmentation using MCMC: application to missing values imputation on cancer medication data.” 2017. Web. 09 Jul 2020.

Vancouver:

Ndlela TI. Bayesian data augmentation using MCMC: application to missing values imputation on cancer medication data. [Internet] [Thesis]. University of KwaZulu-Natal; 2017. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/10413/15641.

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

Council of Science Editors:

Ndlela TI. Bayesian data augmentation using MCMC: application to missing values imputation on cancer medication data. [Thesis]. University of KwaZulu-Natal; 2017. Available from: http://hdl.handle.net/10413/15641

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


Youngstown State University

30. Sajja, Sunitha. Data Mining of Medical Datasets with Missing Attributes from Different Sources.

Degree: MSin Mathematics, Department of Mathematics and Statistics, 2010, Youngstown State University

 Two major problems in data mining are 1) dealing with missing values in the datasets used for knowledge discovery, and 2) using one data set… (more)

Subjects/Keywords: Computer Science; data mining; missing attributes; data classification; outliers

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

APA (6th Edition):

Sajja, S. (2010). Data Mining of Medical Datasets with Missing Attributes from Different Sources. (Masters Thesis). Youngstown State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ysu1300298263

Chicago Manual of Style (16th Edition):

Sajja, Sunitha. “Data Mining of Medical Datasets with Missing Attributes from Different Sources.” 2010. Masters Thesis, Youngstown State University. Accessed July 09, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1300298263.

MLA Handbook (7th Edition):

Sajja, Sunitha. “Data Mining of Medical Datasets with Missing Attributes from Different Sources.” 2010. Web. 09 Jul 2020.

Vancouver:

Sajja S. Data Mining of Medical Datasets with Missing Attributes from Different Sources. [Internet] [Masters thesis]. Youngstown State University; 2010. [cited 2020 Jul 09]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ysu1300298263.

Council of Science Editors:

Sajja S. Data Mining of Medical Datasets with Missing Attributes from Different Sources. [Masters Thesis]. Youngstown State University; 2010. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ysu1300298263

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