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Comparision Of Survival Curves Between Cox Proportional Hazards, Random Forests, And Conditional Inference Forests In Survival Analysis, Brandon Weathers, Richard Cutler Dr. 2017 Utah State University

Comparision Of Survival Curves Between Cox Proportional Hazards, Random Forests, And Conditional Inference Forests In Survival Analysis, Brandon Weathers, Richard Cutler Dr.

All Graduate Plan B and other Reports

Survival analysis methods are a mainstay of the biomedical fields but are finding increasing use in other disciplines including finance and engineering. A widely used tool in survival analysis is the Cox proportional hazards regression model. For this model, all the predicted survivor curves have the same basic shape, which may not be a good approximation to reality. In contrast the Random Survival Forests does not make the proportional hazards assumption and has the flexibility to model survivor curves that are of quite different shapes for different groups of subjects. We applied both techniques to a number of publicly available ...


Sidz Dc Article April Twenty, Sidney Twentythree Sr., Ann Test 2017 bepress university libraries

Sidz Dc Article April Twenty, Sidney Twentythree Sr., Ann Test

Ann Test

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Novel Computational Methods For Censored Data And Regression, Yifan Yang 2017 University of Kentucky

Novel Computational Methods For Censored Data And Regression, Yifan Yang

Theses and Dissertations--Statistics

This dissertation can be divided into three topics. In the first topic, we derived a recursive algorithm for the constrained Kaplan-Meier estimator, which promotes the computation speed up to fifty times compared to the current method that uses EM algorithm. We also showed how this leads to the vast improvement of empirical likelihood analysis with right censored data. After a brief review of regularized regressions, we investigated the computational problems in the parametric/non-parametric hybrid accelerated failure time models and its regularization in a high dimensional setting. We also illustrated that, when the number of pieces increases, the discussed models ...


Joint Modelling In Liver Transplantation, Elizabeth M. Renouf 2016 The University of Western Ontario

Joint Modelling In Liver Transplantation, Elizabeth M. Renouf

Electronic Thesis and Dissertation Repository

In the setting of liver transplantation, clinical trials and transplant registries regularly collect repeated measurements of clinical biomarkers which may be strongly associated with a time-to-event such as graft failure or disease recurrence. Multiple time-to-event outcomes are routinely collected. However, joint models are rarely used. This thesis will describe important considerations for joint modelling in the setting of liver transplantation. We will focus on transplant registry data from the United States. We develop a new tool for joint modelling in the context where a critical health event can be tracked in the longitudinal biomarker and often presents as a non-linear ...


Another Coauthor Test Here, Sid Twentythree, Sid B. Testeroni 2016 bepress university

Another Coauthor Test Here, Sid Twentythree, Sid B. Testeroni

Sid Testeroni

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Conditional Screening For Ultra-High Dimensional Covariates With Survival Outcomes, Hyokyoung Grace Hong, Jian Kang, Yi Li 2016 Michigan State University

Conditional Screening For Ultra-High Dimensional Covariates With Survival Outcomes, Hyokyoung Grace Hong, Jian Kang, Yi Li

The University of Michigan Department of Biostatistics Working Paper Series

Identifying important biomarkers that are predictive for cancer patients' prognosis is key in gaining better insights into the biological influences on the disease and has become a critical component of precision medicine. The emergence of large-scale biomedical survival studies, which typically involve excessive number of biomarkers, has brought high demand in designing efficient screening tools for selecting predictive biomarkers. The vast amount of biomarkers defies any existing variable selection methods via regularization. The recently developed variable screening methods, though powerful in many practical setting, fail to incorporate prior information on the importance of each biomarker and are less powerful in ...


Parallel Evolution Of Character Displacement Driven By Competitive Selection In Terrestrial Salamanders, Dean C. Adams 2016 Iowa State University

Parallel Evolution Of Character Displacement Driven By Competitive Selection In Terrestrial Salamanders, Dean C. Adams

Dean C. Adams

Parallel evolution can occur when common environmental factors exert similar selective forces on morphological variation in populations in different geographic localities. Competition can also generate morphological shifts, and if competing species co-occur in multiple geographic regions, then repeated instances of competitively-driven morphological divergence (character displacement) can occur. Despite the importance of character displacement for inferring the role of selection in morphological evolution however, replicated instances of sympatric morphological divergence are understudied. I tested the hypothesis that interspecific competition generated patterns of parallel morphological divergence in multiple geographic locations where two competing salamander species, Plethodon jordani and P. teyahalee, come into ...


Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret 2016 University of Washington - Seattle Campus

Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret

UW Biostatistics Working Paper Series

We have frequently implemented crossover studies to evaluate new therapeutic interventions for genital herpes simplex virus infection. The outcome measured to assess the efficacy of interventions on herpes disease severity is the viral shedding rate, defined as the frequency of detection of HSV on the genital skin and mucosa. We performed a simulation study to ascertain whether our standard model, which we have used previously, was appropriately considering all the necessary features of the shedding data to provide correct inference. We simulated shedding data under our standard, validated assumptions and assessed the ability of 5 different models to reproduce the ...


Empirical Likelihood And Differentiable Functionals, Zhiyuan Shen 2016 University of Kentucky

Empirical Likelihood And Differentiable Functionals, Zhiyuan Shen

Theses and Dissertations--Statistics

Empirical likelihood (EL) is a recently developed nonparametric method of statistical inference. It has been shown by Owen (1988,1990) and many others that empirical likelihood ratio (ELR) method can be used to produce nice confidence intervals or regions. Owen (1988) shows that -2logELR converges to a chi-square distribution with one degree of freedom subject to a linear statistical functional in terms of distribution functions. However, a generalization of Owen's result to the right censored data setting is difficult since no explicit maximization can be obtained under constraint in terms of distribution functions. Pan and Zhou (2002), instead ...


Statistical Methods For Environmental Exposure Data Subject To Detection Limits, Yuchen Yang 2016 University of Kentucky

Statistical Methods For Environmental Exposure Data Subject To Detection Limits, Yuchen Yang

Theses and Dissertations--Statistics

In this dissertation, we develop unified and efficient nonparametric statistical methods for estimating and comparing environmental exposure distributions in presence of detection limits. In the first part, we propose a kernel-smoothed nonparametric estimator for the exposure distribution without imposing any independence assumption between the exposure level and detection limit. We show that the proposed estimator is consistent and asymptotically normal. Simulation studies demonstrate that the proposed estimator performs well in practical situations. A colon cancer study is provided for illustration. In the second part, we develop a class of test statistics to compare exposure distributions between two groups by using ...


Introduction To The Analysis Of Survival Data In The Presence Of Competing Risks, Peter Austin, Douglas Lee, Jason Fine 2015 Institute for Clinical Evaluative Sciences

Introduction To The Analysis Of Survival Data In The Presence Of Competing Risks, Peter Austin, Douglas Lee, Jason Fine

Peter Austin

Competing risks occur frequently in the analysis of survival data. A competing risk is an event whose occurrence precludes the occurrence of the primary event of interest. In a study examining time to death attributable to cardiovascular causes, death attributable to noncardiovascular causes is a competing risk. When estimating the crude incidence of outcomes, analysts should use the cumulative incidence function, rather than the complement of the Kaplan-Meier survival function. The use of the Kaplan-Meier survival function results in estimates of incidence that are biased upward, regardless of whether the competing events are independent of one another. When fitting regression ...


Doubly Robust And Efficient Estimation Of Marginal Structural Models For The Hazard Function, Wenjing Zheng, Maya Petersen, Mark van der Laan 2015 University of California, Berkeley

Doubly Robust And Efficient Estimation Of Marginal Structural Models For The Hazard Function, Wenjing Zheng, Maya Petersen, Mark Van Der Laan

Wenjing Zheng

In social and health sciences, many research questions involve understanding the causal effect of a longitudinal treatment on mortality (or time-to-event outcomes in general). Often, treatment status may change in response to past covariates that are risk factors for mortality, and in turn, treatment status may also affect such subsequent covariates. In these situations, Marginal Structural Models (MSMs), introduced by Robins (1997), are well-established and widely used tools to account for time-varying confounding. In particular, a MSM can be used to specify the intervention-specific counterfactual hazard function, i.e. the hazard for the outcome of a subject in an ideal ...


Loss-Based Estimation With Cross-Validation: Applications To Microarray Data Analysis And Motif Finding, Sandrine Dudoit, Mark J. van der Laan, Sunduz Keles, Annette M. Molinaro, Sandra E. Sinisi, Siew Leng Teng 2015 Division of Biostatistics, School of Public Health, University of California, Berkeley

Loss-Based Estimation With Cross-Validation: Applications To Microarray Data Analysis And Motif Finding, Sandrine Dudoit, Mark J. Van Der Laan, Sunduz Keles, Annette M. Molinaro, Sandra E. Sinisi, Siew Leng Teng

Mark J. van der Laan

Current statistical inference problems in genomic data analysis involve parameter estimation for high-dimensional multivariate distributions, with typically unknown and intricate correlation patterns among variables. Addressing these inference questions satisfactorily requires: (i) an intensive and thorough search of the parameter space to generate good candidate estimators, (ii) an approach for selecting an optimal estimator among these candidates, and (iii) a method for reliably assessing the performance of the resulting estimator. We propose a unified loss-based methodology for estimator construction, selection, and performance assessment with cross-validation. In this approach, the parameter of interest is defined as the risk minimizer for a suitable ...


A Note On Empirical Likelihood Inference Of Residual Life Regression, Ying Chen, Yichuan Zhao 2015 Division of Biostatistics, School of Public Health, University of California, Berkeley

A Note On Empirical Likelihood Inference Of Residual Life Regression, Ying Chen, Yichuan Zhao

Yichuan Zhao

Mean residual life function, or life expectancy, is an important function to characterize distribution of residual life. The proportional mean residual life model by Oakes and Dasu (1990) is a regression tool to study the association between life expectancy and its associated covariates. Although semiparametric inference procedures have been proposed in the literature, the accuracy of such procedures may be low when the censoring proportion is relatively large. In this paper, the semiparametric inference procedures are studied with an empirical likelihood ratio method. An empirical likelihood confidence region is constructed for the regression parameters. The proposed method is further compared ...


A Pairwise Likelihood Augmented Estimator For The Cox Model Under Left-Truncation, Fan Wu, Sehee Kim, Jing Qin, Rajiv Saran, Yi Li 2015 University of Michigan - Ann Arbor

A Pairwise Likelihood Augmented Estimator For The Cox Model Under Left-Truncation, Fan Wu, Sehee Kim, Jing Qin, Rajiv Saran, Yi Li

The University of Michigan Department of Biostatistics Working Paper Series

Survival data collected from prevalent cohorts are subject to left-truncation and the analysis is challenging. Conditional approaches for left-truncated data under the Cox model are inefficient as they typically ignore the information in the marginal likelihood of the truncation times. Length-biased sampling methods can improve the estimation efficiency but only when the stationarity assumption of the disease incidence holds, i.e., the truncation distribution is uniform; otherwise they may generate biased estimates. In this paper, we propose a semi-parametric method for the Cox model under general left-truncation, where the truncation distribution is unspecified. Our approach is to make inference based ...


Two Essays In Financial Economics, Kyle J. Putnam 2015 University of New Orleans

Two Essays In Financial Economics, Kyle J. Putnam

University of New Orleans Theses and Dissertations

The following dissertation contains two distinct empirical essays which contribute to the overall field of Financial Economics. Chapter 1, entitled “The Determinants of Dynamic Dependence: An Analysis of Commodity Futures and Equity Markets,” examines the determinants of the dynamic equity-commodity return correlations between five commodity futures sub-sectors (energy, foods and fibers, grains and oilseeds, livestock, and precious metals) and a value-weighted equity market index (S&P 500). The study utilizes the traditional DCC model, as well as three time-varying copulas: (i) the normal copula, (ii) the student’s t copula, and (iii) the rotated-gumbel copula as dependence measures. Subsequently, the ...


Characteristics Of Stem Success: A Survival Analysis Model Of Factors Influencing Time To Graduation Among Undergraduate Stem Majors, Riley K. Acton 2015 Ursinus College

Characteristics Of Stem Success: A Survival Analysis Model Of Factors Influencing Time To Graduation Among Undergraduate Stem Majors, Riley K. Acton

Business and Economics Honors Papers

Producing more graduates in Science, Technology, Engineering, and Mathematics (STEM), as well as ensuring students complete college in a timely manner are both areas of national public policy interest. In order to improve these two outcomes, it is imperative to understand what factors lead undergraduate students to persist in, and ultimately graduate with STEM degrees. This paper uses data from the Beginning Postsecondary Students Longitudinal Study, provided by The National Center of Education Statistics, to model the time to baccalaureate degree among STEM majors using a Cox proportional hazard model.


Uncoupling Lifespan And Healthspan In Caenorhabditis Elegans Longevity Mutants, Ankita Bansal, Lihua Julie Zhu, Kelvin Yen, Heidi A. Tissenbaum 2015 University of Massachusetts Medical School

Uncoupling Lifespan And Healthspan In Caenorhabditis Elegans Longevity Mutants, Ankita Bansal, Lihua Julie Zhu, Kelvin Yen, Heidi A. Tissenbaum

Molecular, Cell and Cancer Biology Publications

Aging research has been very successful at identifying signaling pathways and evolutionarily conserved genes that extend lifespan with the assumption that an increase in lifespan will also increase healthspan. However, it is largely unknown whether we are extending the healthy time of life or simply prolonging a period of frailty with increased incidence of age-associated diseases. Here we use Caenorhabditis elegans, one of the premiere systems for lifespan studies, to determine whether lifespan and healthspan are intrinsically correlated. We conducted multiple cellular and organismal assays on wild type as well as four long-lived mutants (insulin/insulin-like growth factor-1, dietary restriction ...


Empirical Likelihood Confidence Band, Shihong Zhu 2015 University of Kentucky

Empirical Likelihood Confidence Band, Shihong Zhu

Theses and Dissertations--Statistics

The confidence band represents an important measure of uncertainty associated with a functional estimator and empirical likelihood method has been proved to be a viable approach to constructing confidence bands in many cases. Using the empirical likelihood ratio principle, this dissertation developed simultaneous confidence bands for many functions of fundamental importance in survival analysis, including the survival function, the difference and ratio of survival functions, the hazards ratio function, and other parameters involving residual lifetimes. Covariate adjustment was incorporated under the proportional hazards assumption. The proposed method can be very useful when, for example, an individualized survival function is desired ...


The Performance Of Inverse Probability Of Treatment Weighting (Iptw) And Full Matching On The Propensity Score In The Presence Of Model Misspecification When Estimating The Effect Of Treatment On Survival Outcomes, Peter Austin, Elizabeth Stuart 2014 Institute for Clinical Evaluative Sciences

The Performance Of Inverse Probability Of Treatment Weighting (Iptw) And Full Matching On The Propensity Score In The Presence Of Model Misspecification When Estimating The Effect Of Treatment On Survival Outcomes, Peter Austin, Elizabeth Stuart

Peter Austin

There is increasing interest in estimating the causal effects of treatments using observational data. Propensity-score matching methods are frequently used to adjust for differences in observed characteristics between treated and control individuals in observational studies. Survival or time-to-event outcomes occur frequently in the medical literature, but the use of propensity score methods in survival analysis has not been thoroughly investigated. This paper compares two approaches for estimating the Average Treatment Effect (ATE) on survival outcomes: Inverse Probability of Treatment Weighting (IPTW) and full matching. The performance of these methods was compared in an extensive set of simulations that varied the ...


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