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Dept: Biostatistics

You searched for subject:( Outcome). Showing records 1 – 13 of 13 total matches.

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University of Southern California

1. Ge, Tingting. Estimation of treatment effects in randomized clinical trials which involve non-trial departures.

Degree: PhD, Biostatistics, 2010, University of Southern California

 Motivated by a real clinical trial, we consider the problem of estimating the causal treatment effect of a two-arm randomized controlled trial in which some… (more)

Subjects/Keywords: potential outcome; causal estimation

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APA (6th Edition):

Ge, T. (2010). Estimation of treatment effects in randomized clinical trials which involve non-trial departures. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/61494/rec/2503

Chicago Manual of Style (16th Edition):

Ge, Tingting. “Estimation of treatment effects in randomized clinical trials which involve non-trial departures.” 2010. Doctoral Dissertation, University of Southern California. Accessed July 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/61494/rec/2503.

MLA Handbook (7th Edition):

Ge, Tingting. “Estimation of treatment effects in randomized clinical trials which involve non-trial departures.” 2010. Web. 20 Jul 2019.

Vancouver:

Ge T. Estimation of treatment effects in randomized clinical trials which involve non-trial departures. [Internet] [Doctoral dissertation]. University of Southern California; 2010. [cited 2019 Jul 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/61494/rec/2503.

Council of Science Editors:

Ge T. Estimation of treatment effects in randomized clinical trials which involve non-trial departures. [Doctoral Dissertation]. University of Southern California; 2010. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/61494/rec/2503


Virginia Commonwealth University

2. Sinks, Shuxian. Response Adaptive Design using Auxiliary and Primary Outcomes.

Degree: PhD, Biostatistics, 2013, Virginia Commonwealth University

 Response adaptive designs intend to allocate more patients to better treatments without undermining the validity and the integrity of the trial. The immediacy of the… (more)

Subjects/Keywords: Response adaptive design; primary outcome; auxiliary outcome; rare event; delayed response; Biostatistics; Physical Sciences and Mathematics; Statistics and Probability

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APA (6th Edition):

Sinks, S. (2013). Response Adaptive Design using Auxiliary and Primary Outcomes. (Doctoral Dissertation). Virginia Commonwealth University. Retrieved from https://scholarscompass.vcu.edu/etd/572

Chicago Manual of Style (16th Edition):

Sinks, Shuxian. “Response Adaptive Design using Auxiliary and Primary Outcomes.” 2013. Doctoral Dissertation, Virginia Commonwealth University. Accessed July 20, 2019. https://scholarscompass.vcu.edu/etd/572.

MLA Handbook (7th Edition):

Sinks, Shuxian. “Response Adaptive Design using Auxiliary and Primary Outcomes.” 2013. Web. 20 Jul 2019.

Vancouver:

Sinks S. Response Adaptive Design using Auxiliary and Primary Outcomes. [Internet] [Doctoral dissertation]. Virginia Commonwealth University; 2013. [cited 2019 Jul 20]. Available from: https://scholarscompass.vcu.edu/etd/572.

Council of Science Editors:

Sinks S. Response Adaptive Design using Auxiliary and Primary Outcomes. [Doctoral Dissertation]. Virginia Commonwealth University; 2013. Available from: https://scholarscompass.vcu.edu/etd/572


University of Southern California

3. Yang, Fan. Utilizing auxiliary covariate data in epidemiologic studies with binary outcome etd-YangFan-2235_Page_001.

Degree: PhD, Biostatistics, 2014, University of Southern California

 In this dissertation we consider methods for using auxiliary information from a generalized “two-phase” design and analysis problem. A typical configuration of such studies involves… (more)

Subjects/Keywords: auxiliary covariate; binary outcome; subsampling; case-control; estimation; study design

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APA (6th Edition):

Yang, F. (2014). Utilizing auxiliary covariate data in epidemiologic studies with binary outcome etd-YangFan-2235_Page_001. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/361565/rec/7778

Chicago Manual of Style (16th Edition):

Yang, Fan. “Utilizing auxiliary covariate data in epidemiologic studies with binary outcome etd-YangFan-2235_Page_001.” 2014. Doctoral Dissertation, University of Southern California. Accessed July 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/361565/rec/7778.

MLA Handbook (7th Edition):

Yang, Fan. “Utilizing auxiliary covariate data in epidemiologic studies with binary outcome etd-YangFan-2235_Page_001.” 2014. Web. 20 Jul 2019.

Vancouver:

Yang F. Utilizing auxiliary covariate data in epidemiologic studies with binary outcome etd-YangFan-2235_Page_001. [Internet] [Doctoral dissertation]. University of Southern California; 2014. [cited 2019 Jul 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/361565/rec/7778.

Council of Science Editors:

Yang F. Utilizing auxiliary covariate data in epidemiologic studies with binary outcome etd-YangFan-2235_Page_001. [Doctoral Dissertation]. University of Southern California; 2014. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/361565/rec/7778


University of Kansas

4. Garrard, Lili. CLASSICAL AND BAYESIAN INSTRUMENT DEVELOPMENT.

Degree: PhD, Biostatistics, 2016, University of Kansas

 Both patient-reported outcome measures (PROMs) and clinician-reported outcome (ClinRO) measures are recognized as essential tools for advocating patient-centered care, an important driving force behind the… (more)

Subjects/Keywords: Biostatistics; Public health; Nursing; Bayesian leave-one-out cross-validation; Bayesian psychometrics; Clinician-reported outcome measures; Injury falls; OBID; Patient-reported outcome measures

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APA (6th Edition):

Garrard, L. (2016). CLASSICAL AND BAYESIAN INSTRUMENT DEVELOPMENT. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/22504

Chicago Manual of Style (16th Edition):

Garrard, Lili. “CLASSICAL AND BAYESIAN INSTRUMENT DEVELOPMENT.” 2016. Doctoral Dissertation, University of Kansas. Accessed July 20, 2019. http://hdl.handle.net/1808/22504.

MLA Handbook (7th Edition):

Garrard, Lili. “CLASSICAL AND BAYESIAN INSTRUMENT DEVELOPMENT.” 2016. Web. 20 Jul 2019.

Vancouver:

Garrard L. CLASSICAL AND BAYESIAN INSTRUMENT DEVELOPMENT. [Internet] [Doctoral dissertation]. University of Kansas; 2016. [cited 2019 Jul 20]. Available from: http://hdl.handle.net/1808/22504.

Council of Science Editors:

Garrard L. CLASSICAL AND BAYESIAN INSTRUMENT DEVELOPMENT. [Doctoral Dissertation]. University of Kansas; 2016. Available from: http://hdl.handle.net/1808/22504


Boston University

5. Bliss, Caleb Andrew. Sample size re-estimation for superiority clinical trials with a dichotomous outcome using an unblinded estimate of the control group outcome rate.

Degree: PhD, Biostatistics, 2014, Boston University

 Superiority clinical trials are often designed with a planned interim analysis for the purpose of sample size re-estimation (SSR) when limited information is available at… (more)

Subjects/Keywords: Biostatistics; Adaptive design; Clinical trials; Dichotomous outcome; Sample size re-estimation; Superiority trials; Unblinded

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APA (6th Edition):

Bliss, C. A. (2014). Sample size re-estimation for superiority clinical trials with a dichotomous outcome using an unblinded estimate of the control group outcome rate. (Doctoral Dissertation). Boston University. Retrieved from http://hdl.handle.net/2144/14282

Chicago Manual of Style (16th Edition):

Bliss, Caleb Andrew. “Sample size re-estimation for superiority clinical trials with a dichotomous outcome using an unblinded estimate of the control group outcome rate.” 2014. Doctoral Dissertation, Boston University. Accessed July 20, 2019. http://hdl.handle.net/2144/14282.

MLA Handbook (7th Edition):

Bliss, Caleb Andrew. “Sample size re-estimation for superiority clinical trials with a dichotomous outcome using an unblinded estimate of the control group outcome rate.” 2014. Web. 20 Jul 2019.

Vancouver:

Bliss CA. Sample size re-estimation for superiority clinical trials with a dichotomous outcome using an unblinded estimate of the control group outcome rate. [Internet] [Doctoral dissertation]. Boston University; 2014. [cited 2019 Jul 20]. Available from: http://hdl.handle.net/2144/14282.

Council of Science Editors:

Bliss CA. Sample size re-estimation for superiority clinical trials with a dichotomous outcome using an unblinded estimate of the control group outcome rate. [Doctoral Dissertation]. Boston University; 2014. Available from: http://hdl.handle.net/2144/14282


Vanderbilt University

6. Mercaldo, Nathaniel David. Design and Analysis Considerations for Complex Longitudinal and Survey Sampling Studies.

Degree: PhD, Biostatistics, 2017, Vanderbilt University

 Pre-existing cohort data (e.g., electronic health records) are being increasingly available, and the need for novel and efficient uses of these data is paramount due… (more)

Subjects/Keywords: efficient study designs; outcome-dependent sampling; survey analysis; misclassification; electronic health records; R software

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APA (6th Edition):

Mercaldo, N. D. (2017). Design and Analysis Considerations for Complex Longitudinal and Survey Sampling Studies. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://etd.library.vanderbilt.edu/available/etd-09062017-100115/ ;

Chicago Manual of Style (16th Edition):

Mercaldo, Nathaniel David. “Design and Analysis Considerations for Complex Longitudinal and Survey Sampling Studies.” 2017. Doctoral Dissertation, Vanderbilt University. Accessed July 20, 2019. http://etd.library.vanderbilt.edu/available/etd-09062017-100115/ ;.

MLA Handbook (7th Edition):

Mercaldo, Nathaniel David. “Design and Analysis Considerations for Complex Longitudinal and Survey Sampling Studies.” 2017. Web. 20 Jul 2019.

Vancouver:

Mercaldo ND. Design and Analysis Considerations for Complex Longitudinal and Survey Sampling Studies. [Internet] [Doctoral dissertation]. Vanderbilt University; 2017. [cited 2019 Jul 20]. Available from: http://etd.library.vanderbilt.edu/available/etd-09062017-100115/ ;.

Council of Science Editors:

Mercaldo ND. Design and Analysis Considerations for Complex Longitudinal and Survey Sampling Studies. [Doctoral Dissertation]. Vanderbilt University; 2017. Available from: http://etd.library.vanderbilt.edu/available/etd-09062017-100115/ ;


Virginia Commonwealth University

7. Williams, Andre. Stereotype Logit Models for High Dimensional Data.

Degree: PhD, Biostatistics, 2010, Virginia Commonwealth University

 Gene expression studies are of growing importance in the field of medicine. In fact, subtypes within the same disease have been shown to have differing… (more)

Subjects/Keywords: gene expression; ordinal outcome; Biostatistics; Physical Sciences and Mathematics; Statistics and Probability

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APA (6th Edition):

Williams, A. (2010). Stereotype Logit Models for High Dimensional Data. (Doctoral Dissertation). Virginia Commonwealth University. Retrieved from https://scholarscompass.vcu.edu/etd/147

Chicago Manual of Style (16th Edition):

Williams, Andre. “Stereotype Logit Models for High Dimensional Data.” 2010. Doctoral Dissertation, Virginia Commonwealth University. Accessed July 20, 2019. https://scholarscompass.vcu.edu/etd/147.

MLA Handbook (7th Edition):

Williams, Andre. “Stereotype Logit Models for High Dimensional Data.” 2010. Web. 20 Jul 2019.

Vancouver:

Williams A. Stereotype Logit Models for High Dimensional Data. [Internet] [Doctoral dissertation]. Virginia Commonwealth University; 2010. [cited 2019 Jul 20]. Available from: https://scholarscompass.vcu.edu/etd/147.

Council of Science Editors:

Williams A. Stereotype Logit Models for High Dimensional Data. [Doctoral Dissertation]. Virginia Commonwealth University; 2010. Available from: https://scholarscompass.vcu.edu/etd/147


The Ohio State University

8. Bailey, Brittney E. Data analysis and multiple imputation for two-level nested designs.

Degree: PhD, Biostatistics, 2018, The Ohio State University

 This work examined methods to account for the clustering that occurs in nested clinical trial designs, which if ignored when analyzing or imputing data can… (more)

Subjects/Keywords: Biostatistics; Statistics; biostatistics; nested data; cluster randomized trial; clinical trial; missing data; semiparametric; binary outcome; multilevel model; mixed effects; multiple imputation; predictive mean matching

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APA (6th Edition):

Bailey, B. E. (2018). Data analysis and multiple imputation for two-level nested designs. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1531822703002162

Chicago Manual of Style (16th Edition):

Bailey, Brittney E. “Data analysis and multiple imputation for two-level nested designs.” 2018. Doctoral Dissertation, The Ohio State University. Accessed July 20, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1531822703002162.

MLA Handbook (7th Edition):

Bailey, Brittney E. “Data analysis and multiple imputation for two-level nested designs.” 2018. Web. 20 Jul 2019.

Vancouver:

Bailey BE. Data analysis and multiple imputation for two-level nested designs. [Internet] [Doctoral dissertation]. The Ohio State University; 2018. [cited 2019 Jul 20]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1531822703002162.

Council of Science Editors:

Bailey BE. Data analysis and multiple imputation for two-level nested designs. [Doctoral Dissertation]. The Ohio State University; 2018. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1531822703002162

9. Gao, Xin. Causal Modeling with Principal Stratification to Assess Effects of Treatment with Partial Compliance, Noncompliance, and Principal Surrogacy in Longitudinal and Time-to-Event Settings.

Degree: PhD, Biostatistics, 2012, University of Michigan

 Much research in the social and health sciences aims to understand the causal relationship between an intervention and an outcome, and a variety of statistical… (more)

Subjects/Keywords: Causal Modeling; Noncompliance; Partial Compliance; Potential Outcome; Principal Stratification; Surrogacy; Public Health; Health Sciences

…Distribution of clinical outcome by treatment arm given treatment dose tolerance for simulation… …and an outcome, and a variety of statistical methods have been developed to answer these… …by the following three examples: 1) when possibly outcome-dependent non-compliance… …inference to the above three topics under a potential outcome framework with a principal… …stratification approach. One fundamental concept in causal modeling is the potential outcome, which is… 

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APA (6th Edition):

Gao, X. (2012). Causal Modeling with Principal Stratification to Assess Effects of Treatment with Partial Compliance, Noncompliance, and Principal Surrogacy in Longitudinal and Time-to-Event Settings. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/96016

Chicago Manual of Style (16th Edition):

Gao, Xin. “Causal Modeling with Principal Stratification to Assess Effects of Treatment with Partial Compliance, Noncompliance, and Principal Surrogacy in Longitudinal and Time-to-Event Settings.” 2012. Doctoral Dissertation, University of Michigan. Accessed July 20, 2019. http://hdl.handle.net/2027.42/96016.

MLA Handbook (7th Edition):

Gao, Xin. “Causal Modeling with Principal Stratification to Assess Effects of Treatment with Partial Compliance, Noncompliance, and Principal Surrogacy in Longitudinal and Time-to-Event Settings.” 2012. Web. 20 Jul 2019.

Vancouver:

Gao X. Causal Modeling with Principal Stratification to Assess Effects of Treatment with Partial Compliance, Noncompliance, and Principal Surrogacy in Longitudinal and Time-to-Event Settings. [Internet] [Doctoral dissertation]. University of Michigan; 2012. [cited 2019 Jul 20]. Available from: http://hdl.handle.net/2027.42/96016.

Council of Science Editors:

Gao X. Causal Modeling with Principal Stratification to Assess Effects of Treatment with Partial Compliance, Noncompliance, and Principal Surrogacy in Longitudinal and Time-to-Event Settings. [Doctoral Dissertation]. University of Michigan; 2012. Available from: http://hdl.handle.net/2027.42/96016

10. Jiang, Bei. Bayesian Joint Modeling of Longitudinal Trajectories and Health Outcome: A Broad Evaluation of Mean and Variation Features in Risk Profiles and Model Assessments.

Degree: PhD, Biostatistics, 2014, University of Michigan

 This dissertation consists of methodology developments and applications for joint modeling of repeated measurements of health risk factors (i.e., longitudinal trajectories) and health outcome data.… (more)

Subjects/Keywords: Bayesian Joint Modeling of Longitudinal and Health Outcome Data; Long-term Trends and Short-term Variability; Latent Class and Shared Random Effect; Functional Predictor; Outcome-informed Artifact; Independent Sample Validation; Statistics and Numeric Data; Science

…predictor in outcome submodel and AUC1 is obtained by using µ0i ( t) with Jθ1 (t… …outcome submodel. . . . . . . . . . . . . . . . . . . . . 74 Individual trajectories that are… …functional predictor in primary outcome submodel… …37 2.2 (a) Mean Area under the ROC curves for the prediction of outcome and… …a functional predictor in primary outcome submodel. . 70 Estimates of model parameters… 

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APA (6th Edition):

Jiang, B. (2014). Bayesian Joint Modeling of Longitudinal Trajectories and Health Outcome: A Broad Evaluation of Mean and Variation Features in Risk Profiles and Model Assessments. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/107164

Chicago Manual of Style (16th Edition):

Jiang, Bei. “Bayesian Joint Modeling of Longitudinal Trajectories and Health Outcome: A Broad Evaluation of Mean and Variation Features in Risk Profiles and Model Assessments.” 2014. Doctoral Dissertation, University of Michigan. Accessed July 20, 2019. http://hdl.handle.net/2027.42/107164.

MLA Handbook (7th Edition):

Jiang, Bei. “Bayesian Joint Modeling of Longitudinal Trajectories and Health Outcome: A Broad Evaluation of Mean and Variation Features in Risk Profiles and Model Assessments.” 2014. Web. 20 Jul 2019.

Vancouver:

Jiang B. Bayesian Joint Modeling of Longitudinal Trajectories and Health Outcome: A Broad Evaluation of Mean and Variation Features in Risk Profiles and Model Assessments. [Internet] [Doctoral dissertation]. University of Michigan; 2014. [cited 2019 Jul 20]. Available from: http://hdl.handle.net/2027.42/107164.

Council of Science Editors:

Jiang B. Bayesian Joint Modeling of Longitudinal Trajectories and Health Outcome: A Broad Evaluation of Mean and Variation Features in Risk Profiles and Model Assessments. [Doctoral Dissertation]. University of Michigan; 2014. Available from: http://hdl.handle.net/2027.42/107164

11. Sun, Zhichao. Dose-Finding Designs for Early-Phase Clinical Trials and Outcome Dependent Sampling for Longitudinal Studies of Gene-Environment Interaction.

Degree: PhD, Biostatistics, 2016, University of Michigan

 In the first project, we extend the nonparametric biased coin design (BCD) for studying a single agent to a two-stage adaptive procedure that can be… (more)

Subjects/Keywords: study design; early-phase clinical trials; outcome dependent sampling; gene-environment interaction; Statistics and Numeric Data; Science

…Early-Phase Clinical Trials and Outcome Dependent Sampling for Longitudinal Studies of Gene… …propose exposure enriched outcome trajectory dependent designs that can inform sample selection… …by leveraging individual exposure and outcome trajectory, and develop a full conditional… …enriched outcome trajectory dependent design enhances the estimation efficiency and detection… …x29; interaction in that the association between an environmental exposure and an outcome… 

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APA (6th Edition):

Sun, Z. (2016). Dose-Finding Designs for Early-Phase Clinical Trials and Outcome Dependent Sampling for Longitudinal Studies of Gene-Environment Interaction. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/133222

Chicago Manual of Style (16th Edition):

Sun, Zhichao. “Dose-Finding Designs for Early-Phase Clinical Trials and Outcome Dependent Sampling for Longitudinal Studies of Gene-Environment Interaction.” 2016. Doctoral Dissertation, University of Michigan. Accessed July 20, 2019. http://hdl.handle.net/2027.42/133222.

MLA Handbook (7th Edition):

Sun, Zhichao. “Dose-Finding Designs for Early-Phase Clinical Trials and Outcome Dependent Sampling for Longitudinal Studies of Gene-Environment Interaction.” 2016. Web. 20 Jul 2019.

Vancouver:

Sun Z. Dose-Finding Designs for Early-Phase Clinical Trials and Outcome Dependent Sampling for Longitudinal Studies of Gene-Environment Interaction. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2019 Jul 20]. Available from: http://hdl.handle.net/2027.42/133222.

Council of Science Editors:

Sun Z. Dose-Finding Designs for Early-Phase Clinical Trials and Outcome Dependent Sampling for Longitudinal Studies of Gene-Environment Interaction. [Doctoral Dissertation]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/133222

12. Zhang, Hui. Semiparametric Methods for Survival Data with Clustering, Outcome-Dependent Sampling, Dependent Censoring, and External Time-Dependent Covariate.

Degree: PhD, Biostatistics, 2012, University of Michigan

 In this dissertation, we focus on the development of semiparametric methods for estimating proportional hazards models in the presence of non-standard data structures, namely clustering,… (more)

Subjects/Keywords: Case-cohort Study; Clustered Data; Cox Model; Dependent Censoring; Outcome-dependent Sampling; Survival Analysis; Statistics and Numeric Data; Science

…special case of what is known as an outcome-dependent sampling (ODS) design, wherein… …primary outcome of interest is CVD death, and the covariate of interest is day of week (… 

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APA (6th Edition):

Zhang, H. (2012). Semiparametric Methods for Survival Data with Clustering, Outcome-Dependent Sampling, Dependent Censoring, and External Time-Dependent Covariate. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/91398

Chicago Manual of Style (16th Edition):

Zhang, Hui. “Semiparametric Methods for Survival Data with Clustering, Outcome-Dependent Sampling, Dependent Censoring, and External Time-Dependent Covariate.” 2012. Doctoral Dissertation, University of Michigan. Accessed July 20, 2019. http://hdl.handle.net/2027.42/91398.

MLA Handbook (7th Edition):

Zhang, Hui. “Semiparametric Methods for Survival Data with Clustering, Outcome-Dependent Sampling, Dependent Censoring, and External Time-Dependent Covariate.” 2012. Web. 20 Jul 2019.

Vancouver:

Zhang H. Semiparametric Methods for Survival Data with Clustering, Outcome-Dependent Sampling, Dependent Censoring, and External Time-Dependent Covariate. [Internet] [Doctoral dissertation]. University of Michigan; 2012. [cited 2019 Jul 20]. Available from: http://hdl.handle.net/2027.42/91398.

Council of Science Editors:

Zhang H. Semiparametric Methods for Survival Data with Clustering, Outcome-Dependent Sampling, Dependent Censoring, and External Time-Dependent Covariate. [Doctoral Dissertation]. University of Michigan; 2012. Available from: http://hdl.handle.net/2027.42/91398

13. Ding, Ying. Some New Insights about the Accelerated Failure Time Model.

Degree: PhD, Biostatistics, 2010, University of Michigan

 The semiparametric linear model is an important alternative to the Cox proportional hazards model for censored survival outcomes. In this dissertation, we provide some new… (more)

Subjects/Keywords: Accelerated Failure Time Model; Censored Survival Outcome; Intercept Estimation; Sieve Maximum Likelihood Estimation; B-spline; Semiparametric Efficiency; Statistics and Numeric Data; Science

…the outcome variable is subject to right censoring and the error distribution is unspecified… 

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APA (6th Edition):

Ding, Y. (2010). Some New Insights about the Accelerated Failure Time Model. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/76009

Chicago Manual of Style (16th Edition):

Ding, Ying. “Some New Insights about the Accelerated Failure Time Model.” 2010. Doctoral Dissertation, University of Michigan. Accessed July 20, 2019. http://hdl.handle.net/2027.42/76009.

MLA Handbook (7th Edition):

Ding, Ying. “Some New Insights about the Accelerated Failure Time Model.” 2010. Web. 20 Jul 2019.

Vancouver:

Ding Y. Some New Insights about the Accelerated Failure Time Model. [Internet] [Doctoral dissertation]. University of Michigan; 2010. [cited 2019 Jul 20]. Available from: http://hdl.handle.net/2027.42/76009.

Council of Science Editors:

Ding Y. Some New Insights about the Accelerated Failure Time Model. [Doctoral Dissertation]. University of Michigan; 2010. Available from: http://hdl.handle.net/2027.42/76009

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