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Michigan Technological University. Mathematical Sciences. degree granting institution.

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University of Maryland, Baltimore County. Statistics. degree granting institution.

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Baylor University. Statistical Science. degree granting institution.

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Bowman, Adrian William, author.

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Chen, Ziyue, author.

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Cheng, Chen, author.

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Dong, Junyi, author.

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Edirisinghe, Pasan Manuranga, author.

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Ellis, Amanda R., author.

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Fang, Youhan, author.

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Garcia, Jose Alfonso Campillo, author.

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Gauran, Iris Ivy M., author.

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Glotzer, Dylan, author.

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Hosseini, Mina, author.

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Iowa State University. Statistics. degree granting institution.

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Kansas State University. Department of Statistics. degree granting institution.

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Kaukis, Nicholas Armstrong, author.

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Liang, Xiaoyu, author.

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Missouri University of Science and Technology. Mathematics. degree granting institution.

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Natarajan, Balasubramaniam, author.

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Nguyen, Yet, author.

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Northern Illinois University. Mathematical Sciences. degree granting institution.

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Oklahoma State University. Statistics. degree granting institution.

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Purdue University. Computer Sciences. degree granting institution.

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Shen, Lei, author.

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Stanley, Sarah, author.

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State University of New York at Binghamton. Mathematical Sciences. degree granting institution.

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Syring, Nicholas Aaron, author.

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The Ohio State University. Statistics. degree granting institution.

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The University of North Carolina at Chapel Hill. Biostatistics. degree granting institution.

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The University of North Carolina at Chapel Hill. Economics. degree granting institution.

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The University of North Carolina at Chapel Hill. Statistics and Operations Research. degree granting institution.

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The University of Wisconsin - Madison. Statistics. degree granting institution.

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University of Glasgow (United Kingdom). Department not provided. degree granting institution.

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University of Illinois at Chicago. Mathematics, Statistics, and Computer Science. degree granting institution.

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University of Kentucky. Public Health. degree granting institution.

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University of Kentucky. Statistics. degree granting institution.

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University of Windsor (Canada). MATHEMATICS AND STATISTICS. degree granting institution.

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Wang, Yiqing, author.

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Wang, Zhenchuan, author.

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Yan, Donglin, author.

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Yang, Xinlan, author. (orcid)0000-0003-1321-1571

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Zhou, Xuan, author.

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Zhu, Huanhuan, author.

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Cover image for A Dependent Competing Risks Model

A Dependent Competing Risks Model

1.

A Dependent Competing Risks Model

by

Wang, Yiqing, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10686415

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Excerpt:

statistical inference. The proposed models have been illustrated in extensive simulation studies and we apply

Cover image for Beta Regression for Modeling a Covariate-Adjusted ROC

Beta Regression for Modeling a Covariate-Adjusted ROC

2.

Beta Regression for Modeling a Covariate-Adjusted ROC

by

Stanley, Sarah, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10751500

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Excerpt:

-parametric methods for estimating a covariate-adjusted ROC. These methods utilize GLMs for binary data with an

Cover image for Inference in Multivariate Generalized Ornstein-Uhlenbeck Processes With a Change-Point

Inference in Multivariate Generalized Ornstein-Uhlenbeck Processes With a Change-Point

3.

Inference in Multivariate Generalized Ornstein-Uhlenbeck Processes With a Change-Point

by

Shen, Lei, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10816946

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Excerpt:

estimator. Finally, in order to illustrate the performance of the proposed methods in short and medium

Cover image for Variable Selection Methods for Structured Data

Variable Selection Methods for Structured Data

4.

Variable Selection Methods for Structured Data

by

Cheng, Chen, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10283008

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Excerpt:

studies are illustrated by both simulation and real data analysis. Chapter 3 describes future application

Cover image for Utilizing Observations and Ranks in Kernel Estimation

Utilizing Observations and Ranks in Kernel Estimation

5.

Utilizing Observations and Ranks in Kernel Estimation

by

Kaukis, Nicholas Armstrong, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10245457

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methods are explored. Simulation is used to compare the modified estimators to the standard estimators. It

Cover image for Statistical Modeling of Self and Proxy Responses with Gerontological Applications

Statistical Modeling of Self and Proxy Responses with Gerontological Applications

6.

Statistical Modeling of Self and Proxy Responses with Gerontological Applications

by

Hosseini, Mina, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10792414

Format:

Excerpt:

investigated via simulation studies. Both approaches, the WGEE method and the Maximum Likelihood (ML) approach

Cover image for Marginal Distribution Method for Checking Regression Model Assumption

Marginal Distribution Method for Checking Regression Model Assumption

7.

Marginal Distribution Method for Checking Regression Model Assumption

by

Dong, Junyi, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10816722

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Excerpt:

distribution function or on the conditional expectation and thus it is alway valid. I present the simulation

Cover image for Accounting for Matching Uncertainty in Photographic Identification Studies of Wild Animals

Accounting for Matching Uncertainty in Photographic Identification Studies of Wild Animals

8.

Accounting for Matching Uncertainty in Photographic Identification Studies of Wild Animals

by

Ellis, Amanda R., author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10902375

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Excerpt:

computation time when fitting the model. Additionally, methods previously applied to record linkage problems

Cover image for Multiple Hypothesis Testing and RNA-Seq Differential Expression Analysis Accounting for Dependence and Relevant Covariates

Multiple Hypothesis Testing and RNA-Seq Differential Expression Analysis Accounting for Dependence and Relevant Covariates

9.

Multiple Hypothesis Testing and RNA-Seq Differential Expression Analysis Accounting for Dependence and Relevant Covariates

by

Nguyen, Yet, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10790987

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Excerpt:

may be detrimental to RNA-seq analysis. We show through simulation that our methods outperform methods

Cover image for Asymptotic properties of Non-parametric Regression with Beta Kernels

Asymptotic properties of Non-parametric Regression with Beta Kernels

10.

Asymptotic properties of Non-parametric Regression with Beta Kernels

by

Natarajan, Balasubramaniam, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10688559

Format:

Excerpt:

evaluated via both a simulation study and a real data application. The results presented and validated in

Cover image for Generalizing Results from Randomized Trials to Target Population via Weighting Methods Using Propensity Score

Generalizing Results from Randomized Trials to Target Population via Weighting Methods Using Propensity Score

11.

Generalizing Results from Randomized Trials to Target Population via Weighting Methods Using Propensity Score

by

Chen, Ziyue, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10901963

Format:

Excerpt:

general, we show via simulation study that the variance methods perform equally well, but the bootstrap

Cover image for Three Papers on Weak Identification Robust Bootstrap Inference

Three Papers on Weak Identification Robust Bootstrap Inference

12.

Three Papers on Weak Identification Robust Bootstrap Inference

by

Garcia, Jose Alfonso Campillo, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10790666

Format:

Excerpt:

is high dimensional. A simulation exercise shows the benefits of using a robust t-test exposing the

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