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Degree: PhD

You searched for subject:(imputation). Showing records 1 – 30 of 118 total matches.

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Robert Gordon University

1. Nana, Constantine Ntsanyu. Corporate criminal liability in the United Kingdom : determining the appropriate mechanism of imputation.

Degree: PhD, 2009, Robert Gordon University

 The objectives of this thesis are twofold: firstly, demonstrate that the string of contradictions stretching across substantive and procedural corporate criminal law may be avoided… (more)

Subjects/Keywords: 340; Corporate criminal law; Imputation

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APA (6th Edition):

Nana, C. N. (2009). Corporate criminal liability in the United Kingdom : determining the appropriate mechanism of imputation. (Doctoral Dissertation). Robert Gordon University. Retrieved from http://hdl.handle.net/10059/466

Chicago Manual of Style (16th Edition):

Nana, Constantine Ntsanyu. “Corporate criminal liability in the United Kingdom : determining the appropriate mechanism of imputation.” 2009. Doctoral Dissertation, Robert Gordon University. Accessed December 08, 2019. http://hdl.handle.net/10059/466.

MLA Handbook (7th Edition):

Nana, Constantine Ntsanyu. “Corporate criminal liability in the United Kingdom : determining the appropriate mechanism of imputation.” 2009. Web. 08 Dec 2019.

Vancouver:

Nana CN. Corporate criminal liability in the United Kingdom : determining the appropriate mechanism of imputation. [Internet] [Doctoral dissertation]. Robert Gordon University; 2009. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/10059/466.

Council of Science Editors:

Nana CN. Corporate criminal liability in the United Kingdom : determining the appropriate mechanism of imputation. [Doctoral Dissertation]. Robert Gordon University; 2009. Available from: http://hdl.handle.net/10059/466


University of Wollongong

2. Lago, Luise Patricia. Imputation of household survey data using mixed models.

Degree: PhD, 2015, University of Wollongong

  Household surveys collect information about a household and data items relating to one or more people within the household. Developing an efficient strategy for… (more)

Subjects/Keywords: Imputation; mixed models; households; statistics

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APA (6th Edition):

Lago, L. P. (2015). Imputation of household survey data using mixed models. (Doctoral Dissertation). University of Wollongong. Retrieved from ; https://ro.uow.edu.au/theses/4369

Chicago Manual of Style (16th Edition):

Lago, Luise Patricia. “Imputation of household survey data using mixed models.” 2015. Doctoral Dissertation, University of Wollongong. Accessed December 08, 2019. ; https://ro.uow.edu.au/theses/4369.

MLA Handbook (7th Edition):

Lago, Luise Patricia. “Imputation of household survey data using mixed models.” 2015. Web. 08 Dec 2019.

Vancouver:

Lago LP. Imputation of household survey data using mixed models. [Internet] [Doctoral dissertation]. University of Wollongong; 2015. [cited 2019 Dec 08]. Available from: ; https://ro.uow.edu.au/theses/4369.

Council of Science Editors:

Lago LP. Imputation of household survey data using mixed models. [Doctoral Dissertation]. University of Wollongong; 2015. Available from: ; https://ro.uow.edu.au/theses/4369


University of Michigan

3. Das, Sayantan. Next Generation of Genotype Imputation Methods.

Degree: PhD, Biostatistics, 2017, University of Michigan

 In the past several years, we have witnessed numerous human genetic studies that have systematically evaluated the contribution of genetic polymorphisms to various complex diseases,… (more)

Subjects/Keywords: genotype imputation; Genetics; Science

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APA (6th Edition):

Das, S. (2017). Next Generation of Genotype Imputation Methods. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/138466

Chicago Manual of Style (16th Edition):

Das, Sayantan. “Next Generation of Genotype Imputation Methods.” 2017. Doctoral Dissertation, University of Michigan. Accessed December 08, 2019. http://hdl.handle.net/2027.42/138466.

MLA Handbook (7th Edition):

Das, Sayantan. “Next Generation of Genotype Imputation Methods.” 2017. Web. 08 Dec 2019.

Vancouver:

Das S. Next Generation of Genotype Imputation Methods. [Internet] [Doctoral dissertation]. University of Michigan; 2017. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/2027.42/138466.

Council of Science Editors:

Das S. Next Generation of Genotype Imputation Methods. [Doctoral Dissertation]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/138466


Oregon State University

4. Eskelson, Bianca N. I. Examination of imputation methods to estimate status and change of forest attributes from paneled inventory data.

Degree: PhD, Forest Resources, 2008, Oregon State University

 The Forest Inventory and Analysis (FIA) program conducts an annual inventory throughout the United States. In the western United States, 10% of all plots (one… (more)

Subjects/Keywords: nearest neighbor imputation; Forest surveys  – Oregon  – Methodology

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APA (6th Edition):

Eskelson, B. N. I. (2008). Examination of imputation methods to estimate status and change of forest attributes from paneled inventory data. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/10021

Chicago Manual of Style (16th Edition):

Eskelson, Bianca N I. “Examination of imputation methods to estimate status and change of forest attributes from paneled inventory data.” 2008. Doctoral Dissertation, Oregon State University. Accessed December 08, 2019. http://hdl.handle.net/1957/10021.

MLA Handbook (7th Edition):

Eskelson, Bianca N I. “Examination of imputation methods to estimate status and change of forest attributes from paneled inventory data.” 2008. Web. 08 Dec 2019.

Vancouver:

Eskelson BNI. Examination of imputation methods to estimate status and change of forest attributes from paneled inventory data. [Internet] [Doctoral dissertation]. Oregon State University; 2008. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/1957/10021.

Council of Science Editors:

Eskelson BNI. Examination of imputation methods to estimate status and change of forest attributes from paneled inventory data. [Doctoral Dissertation]. Oregon State University; 2008. Available from: http://hdl.handle.net/1957/10021


Oregon State University

5. Amer, Safaa R. Neural network imputation : a new fashion or a good tool.

Degree: PhD, Statistics, 2004, Oregon State University

 Most statistical surveys and data collection studies encounter missing data. A common solution to this problem is to discard observations with missing data while reporting… (more)

Subjects/Keywords: Multiple imputation (Statistics)

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APA (6th Edition):

Amer, S. R. (2004). Neural network imputation : a new fashion or a good tool. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/29926

Chicago Manual of Style (16th Edition):

Amer, Safaa R. “Neural network imputation : a new fashion or a good tool.” 2004. Doctoral Dissertation, Oregon State University. Accessed December 08, 2019. http://hdl.handle.net/1957/29926.

MLA Handbook (7th Edition):

Amer, Safaa R. “Neural network imputation : a new fashion or a good tool.” 2004. Web. 08 Dec 2019.

Vancouver:

Amer SR. Neural network imputation : a new fashion or a good tool. [Internet] [Doctoral dissertation]. Oregon State University; 2004. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/1957/29926.

Council of Science Editors:

Amer SR. Neural network imputation : a new fashion or a good tool. [Doctoral Dissertation]. Oregon State University; 2004. Available from: http://hdl.handle.net/1957/29926


University of Oxford

6. Rombach, Ines. The handling, analysis and reporting of missing data in patient reported outcome measures for randomised controlled trials.

Degree: PhD, 2016, University of Oxford

 Missing data is a potential source of bias in the results of randomised controlled trials (RCTs), which can have a negative impact on guidance derived… (more)

Subjects/Keywords: Multiple imputation; Missing data; Randomised controlled trials

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APA (6th Edition):

Rombach, I. (2016). The handling, analysis and reporting of missing data in patient reported outcome measures for randomised controlled trials. (Doctoral Dissertation). University of Oxford. Retrieved from http://ora.ox.ac.uk/objects/uuid:1d038192-69ca-4d34-9974-1bc092466dee ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.730437

Chicago Manual of Style (16th Edition):

Rombach, Ines. “The handling, analysis and reporting of missing data in patient reported outcome measures for randomised controlled trials.” 2016. Doctoral Dissertation, University of Oxford. Accessed December 08, 2019. http://ora.ox.ac.uk/objects/uuid:1d038192-69ca-4d34-9974-1bc092466dee ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.730437.

MLA Handbook (7th Edition):

Rombach, Ines. “The handling, analysis and reporting of missing data in patient reported outcome measures for randomised controlled trials.” 2016. Web. 08 Dec 2019.

Vancouver:

Rombach I. The handling, analysis and reporting of missing data in patient reported outcome measures for randomised controlled trials. [Internet] [Doctoral dissertation]. University of Oxford; 2016. [cited 2019 Dec 08]. Available from: http://ora.ox.ac.uk/objects/uuid:1d038192-69ca-4d34-9974-1bc092466dee ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.730437.

Council of Science Editors:

Rombach I. The handling, analysis and reporting of missing data in patient reported outcome measures for randomised controlled trials. [Doctoral Dissertation]. University of Oxford; 2016. Available from: http://ora.ox.ac.uk/objects/uuid:1d038192-69ca-4d34-9974-1bc092466dee ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.730437


University of Miami

7. Tang, Fei. Random Forest Missing Data Approaches.

Degree: PhD, Biostatistics (Medicine), 2017, University of Miami

 Random forest (RF) missing data algorithms are an attractive approach for imputing missing data. They have the desirable properties of being able to handle mixed… (more)

Subjects/Keywords: Random Forest; Imputation; MESA data; Missing data

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APA (6th Edition):

Tang, F. (2017). Random Forest Missing Data Approaches. (Doctoral Dissertation). University of Miami. Retrieved from https://scholarlyrepository.miami.edu/oa_dissertations/1852

Chicago Manual of Style (16th Edition):

Tang, Fei. “Random Forest Missing Data Approaches.” 2017. Doctoral Dissertation, University of Miami. Accessed December 08, 2019. https://scholarlyrepository.miami.edu/oa_dissertations/1852.

MLA Handbook (7th Edition):

Tang, Fei. “Random Forest Missing Data Approaches.” 2017. Web. 08 Dec 2019.

Vancouver:

Tang F. Random Forest Missing Data Approaches. [Internet] [Doctoral dissertation]. University of Miami; 2017. [cited 2019 Dec 08]. Available from: https://scholarlyrepository.miami.edu/oa_dissertations/1852.

Council of Science Editors:

Tang F. Random Forest Missing Data Approaches. [Doctoral Dissertation]. University of Miami; 2017. Available from: https://scholarlyrepository.miami.edu/oa_dissertations/1852


Wayne State University

8. Grace, Tammy A. The Impact Of Multiple Imputation On The Type Ii Error Rate Of The T Test.

Degree: PhD, Education Evaluation and Research, 2016, Wayne State University

  ABSTRACT THE IMPACT OF MULTIPLE IMPUTATION ON THE TYPE II ERROR RATE OF THE T TEST by TAMMY A. GRACE August 2016 Advisor: Shlomo… (more)

Subjects/Keywords: Multiple Imputation; T Test; Statistics and Probability

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APA (6th Edition):

Grace, T. A. (2016). The Impact Of Multiple Imputation On The Type Ii Error Rate Of The T Test. (Doctoral Dissertation). Wayne State University. Retrieved from https://digitalcommons.wayne.edu/oa_dissertations/1536

Chicago Manual of Style (16th Edition):

Grace, Tammy A. “The Impact Of Multiple Imputation On The Type Ii Error Rate Of The T Test.” 2016. Doctoral Dissertation, Wayne State University. Accessed December 08, 2019. https://digitalcommons.wayne.edu/oa_dissertations/1536.

MLA Handbook (7th Edition):

Grace, Tammy A. “The Impact Of Multiple Imputation On The Type Ii Error Rate Of The T Test.” 2016. Web. 08 Dec 2019.

Vancouver:

Grace TA. The Impact Of Multiple Imputation On The Type Ii Error Rate Of The T Test. [Internet] [Doctoral dissertation]. Wayne State University; 2016. [cited 2019 Dec 08]. Available from: https://digitalcommons.wayne.edu/oa_dissertations/1536.

Council of Science Editors:

Grace TA. The Impact Of Multiple Imputation On The Type Ii Error Rate Of The T Test. [Doctoral Dissertation]. Wayne State University; 2016. Available from: https://digitalcommons.wayne.edu/oa_dissertations/1536


University of Notre Dame

9. Justin M. Luningham. Evaluating Psychometric and Imputation-Based Methods for Data Integration</h1>.

Degree: PhD, Psychology, 2018, University of Notre Dame

  IDA refers to combining data from independent studies into a concatenated dataset and analyzing the new data jointly (Curran & Hussong, 2009). IDA is… (more)

Subjects/Keywords: Integrative Data Analysis; Multiple Imputation; Genetic Consortia

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APA (6th Edition):

Luningham, J. M. (2018). Evaluating Psychometric and Imputation-Based Methods for Data Integration</h1>. (Doctoral Dissertation). University of Notre Dame. Retrieved from https://curate.nd.edu/show/xd07gq70t5b

Chicago Manual of Style (16th Edition):

Luningham, Justin M.. “Evaluating Psychometric and Imputation-Based Methods for Data Integration</h1>.” 2018. Doctoral Dissertation, University of Notre Dame. Accessed December 08, 2019. https://curate.nd.edu/show/xd07gq70t5b.

MLA Handbook (7th Edition):

Luningham, Justin M.. “Evaluating Psychometric and Imputation-Based Methods for Data Integration</h1>.” 2018. Web. 08 Dec 2019.

Vancouver:

Luningham JM. Evaluating Psychometric and Imputation-Based Methods for Data Integration</h1>. [Internet] [Doctoral dissertation]. University of Notre Dame; 2018. [cited 2019 Dec 08]. Available from: https://curate.nd.edu/show/xd07gq70t5b.

Council of Science Editors:

Luningham JM. Evaluating Psychometric and Imputation-Based Methods for Data Integration</h1>. [Doctoral Dissertation]. University of Notre Dame; 2018. Available from: https://curate.nd.edu/show/xd07gq70t5b

10. Magalhães, Ismenia Blavatsky de. Avaliação de redes Bayesianas para imputação em variáveis qualitativas e quantitativas.

Degree: PhD, Engenharia Mecânica, 2007, University of São Paulo

Redes Bayesianas são estruturas que combinam distribuições de probabilidade e grafos. Apesar das redes Bayesianas terem surgido na década de 80 e as primeiras tentativas… (more)

Subjects/Keywords: Bayesian networks; Imputação; Imputação múltipla; Imputation; Missing data; Multiple imputation; Não resposta; Redes Bayesianas

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APA (6th Edition):

Magalhães, I. B. d. (2007). Avaliação de redes Bayesianas para imputação em variáveis qualitativas e quantitativas. (Doctoral Dissertation). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/3/3132/tde-06072007-145922/ ;

Chicago Manual of Style (16th Edition):

Magalhães, Ismenia Blavatsky de. “Avaliação de redes Bayesianas para imputação em variáveis qualitativas e quantitativas.” 2007. Doctoral Dissertation, University of São Paulo. Accessed December 08, 2019. http://www.teses.usp.br/teses/disponiveis/3/3132/tde-06072007-145922/ ;.

MLA Handbook (7th Edition):

Magalhães, Ismenia Blavatsky de. “Avaliação de redes Bayesianas para imputação em variáveis qualitativas e quantitativas.” 2007. Web. 08 Dec 2019.

Vancouver:

Magalhães IBd. Avaliação de redes Bayesianas para imputação em variáveis qualitativas e quantitativas. [Internet] [Doctoral dissertation]. University of São Paulo; 2007. [cited 2019 Dec 08]. Available from: http://www.teses.usp.br/teses/disponiveis/3/3132/tde-06072007-145922/ ;.

Council of Science Editors:

Magalhães IBd. Avaliação de redes Bayesianas para imputação em variáveis qualitativas e quantitativas. [Doctoral Dissertation]. University of São Paulo; 2007. Available from: http://www.teses.usp.br/teses/disponiveis/3/3132/tde-06072007-145922/ ;


Temple University

11. Ouzienko, Vladimir. Log Linear Models for Prediction and Analysis of Networks.

Degree: PhD, 2012, Temple University

Computer and Information Science

The heightened research activity in the interdisciplinary field of network science can be attributed to the emergence of the social network… (more)

Subjects/Keywords: Computer science; ergm; imputation; temoral networks; weighted networks

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APA (6th Edition):

Ouzienko, V. (2012). Log Linear Models for Prediction and Analysis of Networks. (Doctoral Dissertation). Temple University. Retrieved from http://digital.library.temple.edu/u?/p245801coll10,214763

Chicago Manual of Style (16th Edition):

Ouzienko, Vladimir. “Log Linear Models for Prediction and Analysis of Networks.” 2012. Doctoral Dissertation, Temple University. Accessed December 08, 2019. http://digital.library.temple.edu/u?/p245801coll10,214763.

MLA Handbook (7th Edition):

Ouzienko, Vladimir. “Log Linear Models for Prediction and Analysis of Networks.” 2012. Web. 08 Dec 2019.

Vancouver:

Ouzienko V. Log Linear Models for Prediction and Analysis of Networks. [Internet] [Doctoral dissertation]. Temple University; 2012. [cited 2019 Dec 08]. Available from: http://digital.library.temple.edu/u?/p245801coll10,214763.

Council of Science Editors:

Ouzienko V. Log Linear Models for Prediction and Analysis of Networks. [Doctoral Dissertation]. Temple University; 2012. Available from: http://digital.library.temple.edu/u?/p245801coll10,214763


University of Alberta

12. Barnett, Ryan M. Managing Complex Multivariate Relations in the Presence of Incomplete Spatial Data.

Degree: PhD, Department of Civil and Environmental Engineering, 2015, University of Alberta

 Evaluating the process performance of mining and petroleum operations requires numerical geological models of many related rock properties or variables. Taken together, they provide a… (more)

Subjects/Keywords: homotopic; modeling; heterotopic; Gaussian; geology; multivariate; imputation; spatial; geostatistics; complex; transformation

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APA (6th Edition):

Barnett, R. M. (2015). Managing Complex Multivariate Relations in the Presence of Incomplete Spatial Data. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/5t34sn54w

Chicago Manual of Style (16th Edition):

Barnett, Ryan M. “Managing Complex Multivariate Relations in the Presence of Incomplete Spatial Data.” 2015. Doctoral Dissertation, University of Alberta. Accessed December 08, 2019. https://era.library.ualberta.ca/files/5t34sn54w.

MLA Handbook (7th Edition):

Barnett, Ryan M. “Managing Complex Multivariate Relations in the Presence of Incomplete Spatial Data.” 2015. Web. 08 Dec 2019.

Vancouver:

Barnett RM. Managing Complex Multivariate Relations in the Presence of Incomplete Spatial Data. [Internet] [Doctoral dissertation]. University of Alberta; 2015. [cited 2019 Dec 08]. Available from: https://era.library.ualberta.ca/files/5t34sn54w.

Council of Science Editors:

Barnett RM. Managing Complex Multivariate Relations in the Presence of Incomplete Spatial Data. [Doctoral Dissertation]. University of Alberta; 2015. Available from: https://era.library.ualberta.ca/files/5t34sn54w


Washington University in St. Louis

13. Lin, Peng. New methods for discovering common and rare genetic variants in human disease.

Degree: PhD, Biology and Biomedical Sciences: Human and Statistical Genetics, 2011, Washington University in St. Louis

 Since the discovery of Mendel's laws, one of the most challenging problems in genetic research has been to locate and characterize genetic variants that cause… (more)

Subjects/Keywords: Biostatistics; Genetics; Alcohol dependence; CNV accuracy; Collapsing; Imputation accuracy; Rare variants

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APA (6th Edition):

Lin, P. (2011). New methods for discovering common and rare genetic variants in human disease. (Doctoral Dissertation). Washington University in St. Louis. Retrieved from https://openscholarship.wustl.edu/etd/606

Chicago Manual of Style (16th Edition):

Lin, Peng. “New methods for discovering common and rare genetic variants in human disease.” 2011. Doctoral Dissertation, Washington University in St. Louis. Accessed December 08, 2019. https://openscholarship.wustl.edu/etd/606.

MLA Handbook (7th Edition):

Lin, Peng. “New methods for discovering common and rare genetic variants in human disease.” 2011. Web. 08 Dec 2019.

Vancouver:

Lin P. New methods for discovering common and rare genetic variants in human disease. [Internet] [Doctoral dissertation]. Washington University in St. Louis; 2011. [cited 2019 Dec 08]. Available from: https://openscholarship.wustl.edu/etd/606.

Council of Science Editors:

Lin P. New methods for discovering common and rare genetic variants in human disease. [Doctoral Dissertation]. Washington University in St. Louis; 2011. Available from: https://openscholarship.wustl.edu/etd/606


Vanderbilt University

14. Mercaldo, Sarah Fletcher. On Optimal Prediction Rules With Prospective Missingness and Bagged Empirical Null Inference in Large-Scale Data.

Degree: PhD, Biostatistics, 2017, Vanderbilt University

 This dissertation consists of three papers related to missing data, prediction, and large scale inference. The first paper defines the problem of obtaining predictions from… (more)

Subjects/Keywords: missing data; imputation; prediction models; large-scale inference; p-values

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APA (6th Edition):

Mercaldo, S. F. (2017). On Optimal Prediction Rules With Prospective Missingness and Bagged Empirical Null Inference in Large-Scale Data. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://etd.library.vanderbilt.edu/available/etd-09062017-101455/ ;

Chicago Manual of Style (16th Edition):

Mercaldo, Sarah Fletcher. “On Optimal Prediction Rules With Prospective Missingness and Bagged Empirical Null Inference in Large-Scale Data.” 2017. Doctoral Dissertation, Vanderbilt University. Accessed December 08, 2019. http://etd.library.vanderbilt.edu/available/etd-09062017-101455/ ;.

MLA Handbook (7th Edition):

Mercaldo, Sarah Fletcher. “On Optimal Prediction Rules With Prospective Missingness and Bagged Empirical Null Inference in Large-Scale Data.” 2017. Web. 08 Dec 2019.

Vancouver:

Mercaldo SF. On Optimal Prediction Rules With Prospective Missingness and Bagged Empirical Null Inference in Large-Scale Data. [Internet] [Doctoral dissertation]. Vanderbilt University; 2017. [cited 2019 Dec 08]. Available from: http://etd.library.vanderbilt.edu/available/etd-09062017-101455/ ;.

Council of Science Editors:

Mercaldo SF. On Optimal Prediction Rules With Prospective Missingness and Bagged Empirical Null Inference in Large-Scale Data. [Doctoral Dissertation]. Vanderbilt University; 2017. Available from: http://etd.library.vanderbilt.edu/available/etd-09062017-101455/ ;


University of Minnesota

15. Medhanie, Amanuel Gebri. The robustness of multilevel multiple imputation for handling missing data in hierarchical linear models.

Degree: PhD, Educational Psychology, 2013, University of Minnesota

 Missing data often present problems for credible statistical analyses. Luckily there are valid methods for dealing with missing data but the context in which the… (more)

Subjects/Keywords: Hierarchical linear models; Missing data; Multilevel; Multiple imputation; Nested data; PAN

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APA (6th Edition):

Medhanie, A. G. (2013). The robustness of multilevel multiple imputation for handling missing data in hierarchical linear models. (Doctoral Dissertation). University of Minnesota. Retrieved from http://purl.umn.edu/155986

Chicago Manual of Style (16th Edition):

Medhanie, Amanuel Gebri. “The robustness of multilevel multiple imputation for handling missing data in hierarchical linear models.” 2013. Doctoral Dissertation, University of Minnesota. Accessed December 08, 2019. http://purl.umn.edu/155986.

MLA Handbook (7th Edition):

Medhanie, Amanuel Gebri. “The robustness of multilevel multiple imputation for handling missing data in hierarchical linear models.” 2013. Web. 08 Dec 2019.

Vancouver:

Medhanie AG. The robustness of multilevel multiple imputation for handling missing data in hierarchical linear models. [Internet] [Doctoral dissertation]. University of Minnesota; 2013. [cited 2019 Dec 08]. Available from: http://purl.umn.edu/155986.

Council of Science Editors:

Medhanie AG. The robustness of multilevel multiple imputation for handling missing data in hierarchical linear models. [Doctoral Dissertation]. University of Minnesota; 2013. Available from: http://purl.umn.edu/155986


University of Rochester

16. Hebert, Donald Joseph. Global Tests for Multiple Outcomes in Randomized Trials.

Degree: PhD, 2016, University of Rochester

 Methods for analyses of multiple outcome variables in randomized trials are prevalent throughout the statistical literature. Research for the case where the interest is in… (more)

Subjects/Keywords: Global testing; Multiples outcomes; Missing data; Linear combinations; Multiple imputation

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APA (6th Edition):

Hebert, D. J. (2016). Global Tests for Multiple Outcomes in Randomized Trials. (Doctoral Dissertation). University of Rochester. Retrieved from http://hdl.handle.net/1802/31567

Chicago Manual of Style (16th Edition):

Hebert, Donald Joseph. “Global Tests for Multiple Outcomes in Randomized Trials.” 2016. Doctoral Dissertation, University of Rochester. Accessed December 08, 2019. http://hdl.handle.net/1802/31567.

MLA Handbook (7th Edition):

Hebert, Donald Joseph. “Global Tests for Multiple Outcomes in Randomized Trials.” 2016. Web. 08 Dec 2019.

Vancouver:

Hebert DJ. Global Tests for Multiple Outcomes in Randomized Trials. [Internet] [Doctoral dissertation]. University of Rochester; 2016. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/1802/31567.

Council of Science Editors:

Hebert DJ. Global Tests for Multiple Outcomes in Randomized Trials. [Doctoral Dissertation]. University of Rochester; 2016. Available from: http://hdl.handle.net/1802/31567


University of Michigan

17. Zhu, Jian. Assessment and Improvement of a Sequential Regression Multivariate Imputation Algorithm.

Degree: PhD, Biostatistics, 2016, University of Michigan

 The sequential regression multivariate imputation (SRMI, also known as chained equations or fully conditional specifications) is a popular approach for handling missing values in highly… (more)

Subjects/Keywords: Missing Data Multiple Imputation; Sequential Regression Multivariate Imputation; Compatible Conditional Specifications; Block-specific Sequential Regression Multivariate Imputation; Sequential Regression Multivariate Imputation by Quasi-Likelihood Regression Models; Statistics and Numeric Data; Science

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APA (6th Edition):

Zhu, J. (2016). Assessment and Improvement of a Sequential Regression Multivariate Imputation Algorithm. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/133402

Chicago Manual of Style (16th Edition):

Zhu, Jian. “Assessment and Improvement of a Sequential Regression Multivariate Imputation Algorithm.” 2016. Doctoral Dissertation, University of Michigan. Accessed December 08, 2019. http://hdl.handle.net/2027.42/133402.

MLA Handbook (7th Edition):

Zhu, Jian. “Assessment and Improvement of a Sequential Regression Multivariate Imputation Algorithm.” 2016. Web. 08 Dec 2019.

Vancouver:

Zhu J. Assessment and Improvement of a Sequential Regression Multivariate Imputation Algorithm. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/2027.42/133402.

Council of Science Editors:

Zhu J. Assessment and Improvement of a Sequential Regression Multivariate Imputation Algorithm. [Doctoral Dissertation]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/133402


University of Michigan

18. Beesley, Lauren. Missing Data and Variable Selection Methods for Cure Models in Cancer Research.

Degree: PhD, Biostatistics, 2018, University of Michigan

 In survival analysis, a common assumption is that all subjects will eventually experience the event of interest given long enough follow-up time. However, there are… (more)

Subjects/Keywords: cure models; multiple imputation; cancer modeling; Public Health; Health Sciences

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APA (6th Edition):

Beesley, L. (2018). Missing Data and Variable Selection Methods for Cure Models in Cancer Research. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/144010

Chicago Manual of Style (16th Edition):

Beesley, Lauren. “Missing Data and Variable Selection Methods for Cure Models in Cancer Research.” 2018. Doctoral Dissertation, University of Michigan. Accessed December 08, 2019. http://hdl.handle.net/2027.42/144010.

MLA Handbook (7th Edition):

Beesley, Lauren. “Missing Data and Variable Selection Methods for Cure Models in Cancer Research.” 2018. Web. 08 Dec 2019.

Vancouver:

Beesley L. Missing Data and Variable Selection Methods for Cure Models in Cancer Research. [Internet] [Doctoral dissertation]. University of Michigan; 2018. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/2027.42/144010.

Council of Science Editors:

Beesley L. Missing Data and Variable Selection Methods for Cure Models in Cancer Research. [Doctoral Dissertation]. University of Michigan; 2018. Available from: http://hdl.handle.net/2027.42/144010

19. Ramnarine, Shelina Raynell. Genetic Imputation: Accuracy to Application.

Degree: PhD, Biology & Biomedical Sciences (Human & Statistical Genetics), 2016, Washington University in St. Louis

  Genotype imputation, the process of inferring genotypes for untyped variants, is used to identify and refine genetic association findings. This body of work focuses… (more)

Subjects/Keywords: Imputation, Imputation Accuracy, Nicotine Dependence; Genetics; Statistics and Probability

…Chapter 2: When Does Choice of Accuracy Measure Alter Imputation Accuracy Assessments… …vii Abstract of the Dissertation Genetic Imputation: Accuracy to Application by… …Saccone, Chair Genotype imputation, the process of inferring genotypes for untyped variants… …assessing imputation accuracy and uses imputed data to identify genetic contributors to… …Prior work has shown that the Imputation Quality Score (IQS), which is based on… 

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APA (6th Edition):

Ramnarine, S. R. (2016). Genetic Imputation: Accuracy to Application. (Doctoral Dissertation). Washington University in St. Louis. Retrieved from https://openscholarship.wustl.edu/art_sci_etds/759

Chicago Manual of Style (16th Edition):

Ramnarine, Shelina Raynell. “Genetic Imputation: Accuracy to Application.” 2016. Doctoral Dissertation, Washington University in St. Louis. Accessed December 08, 2019. https://openscholarship.wustl.edu/art_sci_etds/759.

MLA Handbook (7th Edition):

Ramnarine, Shelina Raynell. “Genetic Imputation: Accuracy to Application.” 2016. Web. 08 Dec 2019.

Vancouver:

Ramnarine SR. Genetic Imputation: Accuracy to Application. [Internet] [Doctoral dissertation]. Washington University in St. Louis; 2016. [cited 2019 Dec 08]. Available from: https://openscholarship.wustl.edu/art_sci_etds/759.

Council of Science Editors:

Ramnarine SR. Genetic Imputation: Accuracy to Application. [Doctoral Dissertation]. Washington University in St. Louis; 2016. Available from: https://openscholarship.wustl.edu/art_sci_etds/759


University of Stirling

20. Gheyas, Iffat A. Novel Computationally Intelligent Machine Learning Algorithms for Data Mining and Knowledge Discovery.

Degree: PhD, School of Natural Sciences, 2009, University of Stirling

 This thesis addresses three major issues in data mining regarding feature subset selection in large dimensionality domains, plausible reconstruction of incomplete data in cross-sectional applications,… (more)

Subjects/Keywords: Feature SubsetSselection; Missing value impuation; Single Imputation; Multiple Imputation; Dimensionality Reduction; Time Series Forecasting; Curse of Dimensionality; Neural Networks; Evolutionary Algorithm; Data mining; Internet searching; Machine learning

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APA (6th Edition):

Gheyas, I. A. (2009). Novel Computationally Intelligent Machine Learning Algorithms for Data Mining and Knowledge Discovery. (Doctoral Dissertation). University of Stirling. Retrieved from http://hdl.handle.net/1893/2152

Chicago Manual of Style (16th Edition):

Gheyas, Iffat A. “Novel Computationally Intelligent Machine Learning Algorithms for Data Mining and Knowledge Discovery.” 2009. Doctoral Dissertation, University of Stirling. Accessed December 08, 2019. http://hdl.handle.net/1893/2152.

MLA Handbook (7th Edition):

Gheyas, Iffat A. “Novel Computationally Intelligent Machine Learning Algorithms for Data Mining and Knowledge Discovery.” 2009. Web. 08 Dec 2019.

Vancouver:

Gheyas IA. Novel Computationally Intelligent Machine Learning Algorithms for Data Mining and Knowledge Discovery. [Internet] [Doctoral dissertation]. University of Stirling; 2009. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/1893/2152.

Council of Science Editors:

Gheyas IA. Novel Computationally Intelligent Machine Learning Algorithms for Data Mining and Knowledge Discovery. [Doctoral Dissertation]. University of Stirling; 2009. Available from: http://hdl.handle.net/1893/2152


University of Alberta

21. Deutsch, Jared L. Multivariate Spatial Modeling of Metallurgical Rock Properties.

Degree: PhD, Department of Civil and Environmental Engineering, 2015, University of Alberta

 High resolution spatial numerical models of metallurgical properties constrained by geological controls and more extensively measured grade and geomechanical properties constitute an important part of… (more)

Subjects/Keywords: Multivariate simulation; Geometallurgy; Geostatistics; Parameter uncertainty; Nonlinear variables; Multiscale modeling; Multiple imputation; Unequal sampling

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APA (6th Edition):

Deutsch, J. L. (2015). Multivariate Spatial Modeling of Metallurgical Rock Properties. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/c1r66j118w

Chicago Manual of Style (16th Edition):

Deutsch, Jared L. “Multivariate Spatial Modeling of Metallurgical Rock Properties.” 2015. Doctoral Dissertation, University of Alberta. Accessed December 08, 2019. https://era.library.ualberta.ca/files/c1r66j118w.

MLA Handbook (7th Edition):

Deutsch, Jared L. “Multivariate Spatial Modeling of Metallurgical Rock Properties.” 2015. Web. 08 Dec 2019.

Vancouver:

Deutsch JL. Multivariate Spatial Modeling of Metallurgical Rock Properties. [Internet] [Doctoral dissertation]. University of Alberta; 2015. [cited 2019 Dec 08]. Available from: https://era.library.ualberta.ca/files/c1r66j118w.

Council of Science Editors:

Deutsch JL. Multivariate Spatial Modeling of Metallurgical Rock Properties. [Doctoral Dissertation]. University of Alberta; 2015. Available from: https://era.library.ualberta.ca/files/c1r66j118w


University of Kansas

22. Kim, Min Sung. Linking with Planned Missing Data: Concurrent Calibration with Multiple Imputation.

Degree: PhD, Psychology & Research in Education, 2015, University of Kansas

 The purpose of this paper is to introduce a new Item Response Theory (IRT) concurrent calibration method using multiple imputation and investigate its effectiveness by… (more)

Subjects/Keywords: Educational psychology; Educational tests & measurements; Educational evaluation; concurrent calibration; equating; IRT; linking; multiple imputation

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APA (6th Edition):

Kim, M. S. (2015). Linking with Planned Missing Data: Concurrent Calibration with Multiple Imputation. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/20985

Chicago Manual of Style (16th Edition):

Kim, Min Sung. “Linking with Planned Missing Data: Concurrent Calibration with Multiple Imputation.” 2015. Doctoral Dissertation, University of Kansas. Accessed December 08, 2019. http://hdl.handle.net/1808/20985.

MLA Handbook (7th Edition):

Kim, Min Sung. “Linking with Planned Missing Data: Concurrent Calibration with Multiple Imputation.” 2015. Web. 08 Dec 2019.

Vancouver:

Kim MS. Linking with Planned Missing Data: Concurrent Calibration with Multiple Imputation. [Internet] [Doctoral dissertation]. University of Kansas; 2015. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/1808/20985.

Council of Science Editors:

Kim MS. Linking with Planned Missing Data: Concurrent Calibration with Multiple Imputation. [Doctoral Dissertation]. University of Kansas; 2015. Available from: http://hdl.handle.net/1808/20985


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 December 08, 2019. 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. 08 Dec 2019.

Vancouver:

Parsons MM. Planned Missing Data Designs in Communication Research. [Internet] [Doctoral dissertation]. Ohio University; 2013. [cited 2019 Dec 08]. 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


Georgia State University

24. Alemdar, Meltem. A Monte Carlo Study: The Impact of Missing Data in Cross-Classification Random Effects Models.

Degree: PhD, Educational Policy Studies, 2009, Georgia State University

 Unlike multilevel data with a purely nested structure, data that are cross-classified not only may be clustered into hierarchically ordered units but also may belong… (more)

Subjects/Keywords: Cross- Classified Data; Cross-Classified Random Effects Models; Missing Data; Multiple Imputation; Education; Education Policy

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APA (6th Edition):

Alemdar, M. (2009). A Monte Carlo Study: The Impact of Missing Data in Cross-Classification Random Effects Models. (Doctoral Dissertation). Georgia State University. Retrieved from https://scholarworks.gsu.edu/eps_diss/34

Chicago Manual of Style (16th Edition):

Alemdar, Meltem. “A Monte Carlo Study: The Impact of Missing Data in Cross-Classification Random Effects Models.” 2009. Doctoral Dissertation, Georgia State University. Accessed December 08, 2019. https://scholarworks.gsu.edu/eps_diss/34.

MLA Handbook (7th Edition):

Alemdar, Meltem. “A Monte Carlo Study: The Impact of Missing Data in Cross-Classification Random Effects Models.” 2009. Web. 08 Dec 2019.

Vancouver:

Alemdar M. A Monte Carlo Study: The Impact of Missing Data in Cross-Classification Random Effects Models. [Internet] [Doctoral dissertation]. Georgia State University; 2009. [cited 2019 Dec 08]. Available from: https://scholarworks.gsu.edu/eps_diss/34.

Council of Science Editors:

Alemdar M. A Monte Carlo Study: The Impact of Missing Data in Cross-Classification Random Effects Models. [Doctoral Dissertation]. Georgia State University; 2009. Available from: https://scholarworks.gsu.edu/eps_diss/34


University of Bradford

25. Mohd Jamil, J. B. Partial least squares structural equation modelling with incomplete data : an investigation of the impact of imputation methods.

Degree: PhD, 2012, University of Bradford

 Despite considerable advances in missing data imputation methods over the last three decades, the problem of missing data remains largely unsolved. Many techniques have emerged… (more)

Subjects/Keywords: 658; Missing data; Partial least squares; Structural equation modelling; Neural networks; Imputation methods; Incomplete data

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APA (6th Edition):

Mohd Jamil, J. B. (2012). Partial least squares structural equation modelling with incomplete data : an investigation of the impact of imputation methods. (Doctoral Dissertation). University of Bradford. Retrieved from http://hdl.handle.net/10454/5728

Chicago Manual of Style (16th Edition):

Mohd Jamil, J B. “Partial least squares structural equation modelling with incomplete data : an investigation of the impact of imputation methods.” 2012. Doctoral Dissertation, University of Bradford. Accessed December 08, 2019. http://hdl.handle.net/10454/5728.

MLA Handbook (7th Edition):

Mohd Jamil, J B. “Partial least squares structural equation modelling with incomplete data : an investigation of the impact of imputation methods.” 2012. Web. 08 Dec 2019.

Vancouver:

Mohd Jamil JB. Partial least squares structural equation modelling with incomplete data : an investigation of the impact of imputation methods. [Internet] [Doctoral dissertation]. University of Bradford; 2012. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/10454/5728.

Council of Science Editors:

Mohd Jamil JB. Partial least squares structural equation modelling with incomplete data : an investigation of the impact of imputation methods. [Doctoral Dissertation]. University of Bradford; 2012. Available from: http://hdl.handle.net/10454/5728


The Ohio State University

26. Kline, David. Systematically Missing Subject-Level Data in Longitudinal Research Synthesis.

Degree: PhD, Biostatistics, 2015, The Ohio State University

 When conducting research synthesis, the collection of studies that will be combined often do not measure the same set of variables, which creates missing data.… (more)

Subjects/Keywords: Biostatistics; Statistics; multiple imputation; research synthesis; longitudinal data; missing data; individual patient data

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APA (6th Edition):

Kline, D. (2015). Systematically Missing Subject-Level Data in Longitudinal Research Synthesis. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1440067809

Chicago Manual of Style (16th Edition):

Kline, David. “Systematically Missing Subject-Level Data in Longitudinal Research Synthesis.” 2015. Doctoral Dissertation, The Ohio State University. Accessed December 08, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1440067809.

MLA Handbook (7th Edition):

Kline, David. “Systematically Missing Subject-Level Data in Longitudinal Research Synthesis.” 2015. Web. 08 Dec 2019.

Vancouver:

Kline D. Systematically Missing Subject-Level Data in Longitudinal Research Synthesis. [Internet] [Doctoral dissertation]. The Ohio State University; 2015. [cited 2019 Dec 08]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1440067809.

Council of Science Editors:

Kline D. Systematically Missing Subject-Level Data in Longitudinal Research Synthesis. [Doctoral Dissertation]. The Ohio State University; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1440067809


Penn State University

27. Roth, Veronica Leigh. Detecting & Adjusting for Attrition Bias in Longitudinal Survey Panels.

Degree: PhD, Sociology, 2015, Penn State University

 The use of panel studies, in which the same people are interviewed at least twice in two different time periods, provides researchers with the ability… (more)

Subjects/Keywords: attrition; panel conditioning; refreshment panels; multiple imputation; longitudinal panel data; marital quality

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APA (6th Edition):

Roth, V. L. (2015). Detecting & Adjusting for Attrition Bias in Longitudinal Survey Panels. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/26344

Chicago Manual of Style (16th Edition):

Roth, Veronica Leigh. “Detecting & Adjusting for Attrition Bias in Longitudinal Survey Panels.” 2015. Doctoral Dissertation, Penn State University. Accessed December 08, 2019. https://etda.libraries.psu.edu/catalog/26344.

MLA Handbook (7th Edition):

Roth, Veronica Leigh. “Detecting & Adjusting for Attrition Bias in Longitudinal Survey Panels.” 2015. Web. 08 Dec 2019.

Vancouver:

Roth VL. Detecting & Adjusting for Attrition Bias in Longitudinal Survey Panels. [Internet] [Doctoral dissertation]. Penn State University; 2015. [cited 2019 Dec 08]. Available from: https://etda.libraries.psu.edu/catalog/26344.

Council of Science Editors:

Roth VL. Detecting & Adjusting for Attrition Bias in Longitudinal Survey Panels. [Doctoral Dissertation]. Penn State University; 2015. Available from: https://etda.libraries.psu.edu/catalog/26344


University of Edinburgh

28. Corbin, Laura Jayne. Application of genomic technologies to the horse.

Degree: PhD, 2013, University of Edinburgh

 The publication of a draft equine genome sequence and the release by Illumina of a 50,000 marker single-nucleotide polymorphism (SNP) genotyping chip has provided equine… (more)

Subjects/Keywords: 636.1; equine; genome selection; genome-wide association studies; GWAS; imputation; linkage disequilibrium; osteochondrosis; SNP

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APA (6th Edition):

Corbin, L. J. (2013). Application of genomic technologies to the horse. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/11808

Chicago Manual of Style (16th Edition):

Corbin, Laura Jayne. “Application of genomic technologies to the horse.” 2013. Doctoral Dissertation, University of Edinburgh. Accessed December 08, 2019. http://hdl.handle.net/1842/11808.

MLA Handbook (7th Edition):

Corbin, Laura Jayne. “Application of genomic technologies to the horse.” 2013. Web. 08 Dec 2019.

Vancouver:

Corbin LJ. Application of genomic technologies to the horse. [Internet] [Doctoral dissertation]. University of Edinburgh; 2013. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/1842/11808.

Council of Science Editors:

Corbin LJ. Application of genomic technologies to the horse. [Doctoral Dissertation]. University of Edinburgh; 2013. Available from: http://hdl.handle.net/1842/11808


University of Cincinnati

29. Deryol, Rustu. Lifestyle, Self-Control, and School-Based Violent Victimization in Turkey.

Degree: PhD, Education, Criminal Justice, and Human Services: Criminal Justice, 2015, University of Cincinnati

 The present study aims to fill in the gap in the Turkish school-based violent victimization literature by exploring the predictors of general, crime-, and gender-specific… (more)

Subjects/Keywords: Criminology; multiple imputation; school-based victimization; mediation; moderation; gender-specific opportunity; crime-specific opportunity

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APA (6th Edition):

Deryol, R. (2015). Lifestyle, Self-Control, and School-Based Violent Victimization in Turkey. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439308217

Chicago Manual of Style (16th Edition):

Deryol, Rustu. “Lifestyle, Self-Control, and School-Based Violent Victimization in Turkey.” 2015. Doctoral Dissertation, University of Cincinnati. Accessed December 08, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439308217.

MLA Handbook (7th Edition):

Deryol, Rustu. “Lifestyle, Self-Control, and School-Based Violent Victimization in Turkey.” 2015. Web. 08 Dec 2019.

Vancouver:

Deryol R. Lifestyle, Self-Control, and School-Based Violent Victimization in Turkey. [Internet] [Doctoral dissertation]. University of Cincinnati; 2015. [cited 2019 Dec 08]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439308217.

Council of Science Editors:

Deryol R. Lifestyle, Self-Control, and School-Based Violent Victimization in Turkey. [Doctoral Dissertation]. University of Cincinnati; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439308217


University of Edinburgh

30. Tsairidou, Smaragda. Genetics of disease resistance : application to bovine tuberculosis.

Degree: PhD, 2016, University of Edinburgh

 Bovine Tuberculosis (bTB) is a disease of significant economic importance, being one of the most persistent animal health problems in the UK and the Republic… (more)

Subjects/Keywords: 636.2; bovine Tuberculosis; genomic selection; SICCT; Single Intradermal Comparative Cervical Test; prediction accuracy; imputation

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APA (6th Edition):

Tsairidou, S. (2016). Genetics of disease resistance : application to bovine tuberculosis. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/25397

Chicago Manual of Style (16th Edition):

Tsairidou, Smaragda. “Genetics of disease resistance : application to bovine tuberculosis.” 2016. Doctoral Dissertation, University of Edinburgh. Accessed December 08, 2019. http://hdl.handle.net/1842/25397.

MLA Handbook (7th Edition):

Tsairidou, Smaragda. “Genetics of disease resistance : application to bovine tuberculosis.” 2016. Web. 08 Dec 2019.

Vancouver:

Tsairidou S. Genetics of disease resistance : application to bovine tuberculosis. [Internet] [Doctoral dissertation]. University of Edinburgh; 2016. [cited 2019 Dec 08]. Available from: http://hdl.handle.net/1842/25397.

Council of Science Editors:

Tsairidou S. Genetics of disease resistance : application to bovine tuberculosis. [Doctoral Dissertation]. University of Edinburgh; 2016. Available from: http://hdl.handle.net/1842/25397

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