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Causal Inference And Prediction On Observational Data With Survival Outcomes, Xiaofei Chen 2020 Southern Methodist University / UT Southwestern Medical Center

Causal Inference And Prediction On Observational Data With Survival Outcomes, Xiaofei Chen

Statistical Science Theses and Dissertations

Infants with hypoplastic left heart syndrome require an initial Norwood operation, followed some months later by a stage 2 palliation (S2P). The timing of S2P is critical for the operation’s success and the infant’s survival, but the optimal timing, if one exists, is unknown. We attempt to estimate the optimal timing of S2P by analyzing data from the Single Ventricle Reconstruction Trial (SVRT), which randomized patients between two different types of Norwood procedure. In the SVRT, the timing of the S2P was chosen by the medical team; thus with respect to this exposure, the trial constitutes an observational ...


Statistical Models And Analysis Of Univariate And Multivariate Degradation Data, Lochana Palayangoda 2020 Southern Methodist University

Statistical Models And Analysis Of Univariate And Multivariate Degradation Data, Lochana Palayangoda

Statistical Science Theses and Dissertations

For degradation data in reliability analysis, estimation of the first-passage time (FPT) distribution to a threshold provides valuable information on reliability characteristics. Recently, Balakrishnan and Qin (2019; Applied Stochastic Models in Business and Industry, 35:571-590) studied a nonparametric method to approximate the FPT distribution of such degradation processes if the underlying process type is unknown. In this thesis, we propose improved techniques based on saddlepoint approximation, which enhance upon their suggested methods. Numerical examples and Monte Carlo simulation studies are used to illustrate the advantages of the proposed techniques. Limitations of the improved techniques are discussed and some possible ...


The Opioid Crisis And Life Expectancy In The U.S., Gabriel Lozano 2020 University of Pennsylvania

The Opioid Crisis And Life Expectancy In The U.S., Gabriel Lozano

Joseph Wharton Scholars

Since the 1990s, when opioids started to be grossly over-prescribed, almost 450,000 people have died as a direct result of opioid abuse in the United States. This study analyzes the role the opioid crisis has in the decreasing life expectancy in the United States, a troubling trend given the enormous and growing national healthcare expenditure. Employing a multiple decrement model and national life expectancy tables, this paper removes the opioid-related mortality and develops a new life expectancy model. The actuarial analysis of the observed and estimated life expectancies reveals the impact of opioid-related deaths: overall, U.S persons are ...


Rmse-Minimizing Confidence Intervals For The Binomial Parameter, Kexin Feng 2020 William & Mary

Rmse-Minimizing Confidence Intervals For The Binomial Parameter, Kexin Feng

Undergraduate Honors Theses

Let X1, X2, . . . , Xn be independent and identically distributed Bernoulli(p) random variables with unknown parameter p satisfying 0 < p < 1. Let X = Pn i=1 Xi be the number of successes in the n mutually independent Bernoulli trials. The maximum likelihood estimator of p is ˆp = X/n. For fixed n and α, there are n + 1 distinct 100(1 − α)% confidence intervals associated with X = 0, 1, 2, . . . , n. Currently there is no known exact confidence interval for p. Our goal is to construct the confidence interval for p whose actual coverage is closest to the stated coverage, using the root mean squared error, RMSE, to measure the difference between the actual coverage and the stated coverage. The approximate confidence interval for p developed here minimizes the RMSE for a sample size n and a significance level α.


Survival Of White-Tailed Deer Fawns In Central Iowa, Patrick G. McGovern, Stephen J. Dinsmore, Julie A. Blanchong 2020 Iowa State University

Survival Of White-Tailed Deer Fawns In Central Iowa, Patrick G. Mcgovern, Stephen J. Dinsmore, Julie A. Blanchong

Natural Resource Ecology and Management Publications

Understanding demographic parameters such as survival is important for scientifically sound wildlife management. Survival can vary by region, sex, age-class, habitat, and other factors. White-tailed deer fawn survival is highly variable across the species’ range. While recent studies have investigated fawn survival in several Midwestern states, there have been no published estimates from Iowa for 30 years. We radio-collared 48 fawns in central Iowa from 2015–2017 to estimate survival, home range size, and habitat composition and identity causes of mortality. Estimated fawn survival (± SE) was similar to other Midwest studies at 30 (0.78 ± 0.07)) and 60 days ...


Estimating Arthropod Survival Probability From Field Counts: A Case Study With Monarch Butterflies, Tyler J. Grant, D. T. Tyler Flockhart, Teresa R. Blader, Richard L. Hellmich, Grace M. Pitman, Sam Tyner, D. Ryan Norris, Steven P. Bradbury 2020 Iowa State University

Estimating Arthropod Survival Probability From Field Counts: A Case Study With Monarch Butterflies, Tyler J. Grant, D. T. Tyler Flockhart, Teresa R. Blader, Richard L. Hellmich, Grace M. Pitman, Sam Tyner, D. Ryan Norris, Steven P. Bradbury

Entomology Publications

Survival probability is fundamental for understanding population dynamics. Methods for estimating survival probability from field data typically require marking individuals, but marking methods are not possible for arthropod species that molt their exoskeleton between life stages. We developed a novel Bayesian state‐space model to estimate arthropod larval survival probability from stage‐structured count data. We performed simulation studies to evaluate estimation bias due to detection probability, individual variation in stage duration, and study design (sampling frequency and sample size). Estimation of cumulative survival probability from oviposition to pupation was robust to potential sources of bias. Our simulations also provide ...


Conditional Survival Analysis For Concrete Bridge Decks, Azam Nabizadeh, Habib Tabatabai, Mohammad A. Tabatabai 2019 University of Wisconsin-Milwaukee

Conditional Survival Analysis For Concrete Bridge Decks, Azam Nabizadeh, Habib Tabatabai, Mohammad A. Tabatabai

Civil and Environmental Engineering Faculty Articles

Bridge decks are a significant factor in the deterioration of bridges, and substantially affect long-term bridge maintenance decisions. In this study, conditional survival (reliability) analysis techniques are applied to bridge decks to evaluate the age at the end of service life using the National Bridge Inventory records. As bridge decks age, the probability of survival and the expected service life would change. The additional knowledge gained from the fact that a bridge deck has already survived a specific number of years alters (increases) the original probability of survival at subsequent years based on the conditional probability theory. The conditional expected ...


Robustness Of Semi-Parametric Survival Model: Simulation Studies And Application To Clinical Data, Isaac Nwi-Mozu 2019 East Tennessee State University

Robustness Of Semi-Parametric Survival Model: Simulation Studies And Application To Clinical Data, Isaac Nwi-Mozu

Electronic Theses and Dissertations

An efficient way of analyzing survival clinical data such as cancer data is a great concern to health experts. In this study, we investigate and propose an efficient way of handling survival clinical data. Simulation studies were conducted to compare performances of various forms of survival model techniques using an R package ``survsim". Models performance was conducted with varying sample sizes as small ($n5000$). For small and mild samples, the performance of the semi-parametric outperform or approximate the performance of the parametric model. However, for large samples, the parametric model outperforms the semi-parametric model. We compared the effectiveness and reliability ...


Quantifying Sleep Architecture For Pediatric Hypersomnia Conditions, Alicia K. Colclasure 2019 Colorado School of Mines

Quantifying Sleep Architecture For Pediatric Hypersomnia Conditions, Alicia K. Colclasure

Biology and Medicine Through Mathematics Conference

No abstract provided.


Effects Of Perioperative Hyperglycemia In Patients With Diabetes Compared To Patients Without Diabetes: A Retrospective Study Of Treatment And Outcomes, Matthew Anderson 2019 University of Nebraska Medical Center

Effects Of Perioperative Hyperglycemia In Patients With Diabetes Compared To Patients Without Diabetes: A Retrospective Study Of Treatment And Outcomes, Matthew Anderson

Capstone Experience

The main goal of this project was to examine the differences in perioperative hyperglycemia treatment received by patients with a diagnosis of diabetes mellitus (DM) and patients without a diagnosis of diabetes (NDM); and how these treatment differences can affect the length of hospital stay. Studies have revealed that, when comparing DM and NDM patients with the same degree of perioperative hyperglycemia, NDM patients suffer worse outcomes. It has been suggested in previous research that this may be because NDM patients receive treatment that does not measure up to the standard of care treatment that DM patients receive. In this ...


A Bayesian Framework For Estimating Seismic Wave Arrival Time, Hua Zhong 2019 University of Arkansas, Fayetteville

A Bayesian Framework For Estimating Seismic Wave Arrival Time, Hua Zhong

Theses and Dissertations

Because earthquakes have a large impact on human society, statistical methods for better studying earthquakes are required. One characteristic of earthquakes is the arrival time of seismic waves at a seismic signal sensor. Once we can estimate the earthquake arrival time accurately, the earthquake location can be triangulated, and assistance can be sent to that area correctly. This study presents a Bayesian framework to predict the arrival time of seismic waves with associated uncertainty. We use a change point framework to model the different conditions before and after the seismic wave arrives. To evaluate the performance of the model, we ...


Unified Methods For Feature Selection In Large-Scale Genomic Studies With Censored Survival Outcomes, Lauren Spirko-Burns, Karthik Devarajan 2019 Temple University

Unified Methods For Feature Selection In Large-Scale Genomic Studies With Censored Survival Outcomes, Lauren Spirko-Burns, Karthik Devarajan

COBRA Preprint Series

One of the major goals in large-scale genomic studies is to identify genes with a prognostic impact on time-to-event outcomes which provide insight into the disease's process. With rapid developments in high-throughput genomic technologies in the past two decades, the scientific community is able to monitor the expression levels of tens of thousands of genes and proteins resulting in enormous data sets where the number of genomic features is far greater than the number of subjects. Methods based on univariate Cox regression are often used to select genomic features related to survival outcome; however, the Cox model assumes proportional ...


Methods For Evaluating Dropout Attrition In Survey Data, Camille J. Hochheimer 2019 Virginia Commonwealth University

Methods For Evaluating Dropout Attrition In Survey Data, Camille J. Hochheimer

Theses and Dissertations

As researchers increasingly use web-based surveys, the ease of dropping out in the online setting is a growing issue in ensuring data quality. One theory is that dropout or attrition occurs in phases that can be generalized to phases of high dropout and phases of stable use. In order to detect these phases, several methods are explored. First, existing methods and user-specified thresholds are applied to survey data where significant changes in the dropout rate between two questions is interpreted as the start or end of a high dropout phase. Next, survey dropout is considered as a time-to-event outcome and ...


Automatic 13C Chemical Shift Reference Correction Of Protein Nmr Spectral Data Using Data Mining And Bayesian Statistical Modeling, Xi Chen 2019 University of kencutky

Automatic 13C Chemical Shift Reference Correction Of Protein Nmr Spectral Data Using Data Mining And Bayesian Statistical Modeling, Xi Chen

Theses and Dissertations--Molecular and Cellular Biochemistry

Nuclear magnetic resonance (NMR) is a highly versatile analytical technique for studying molecular configuration, conformation, and dynamics, especially of biomacromolecules such as proteins. However, due to the intrinsic properties of NMR experiments, results from the NMR instruments require a refencing step before the down-the-line analysis. Poor chemical shift referencing, especially for 13C in protein Nuclear Magnetic Resonance (NMR) experiments, fundamentally limits and even prevents effective study of biomacromolecules via NMR. There is no available method that can rereference carbon chemical shifts from protein NMR without secondary experimental information such as structure or resonance assignment.

To solve this problem, we ...


Quantifying Human Biological Age: A Machine Learning Approach, Syed Ashiqur Rahman 2019 West Virginia University

Quantifying Human Biological Age: A Machine Learning Approach, Syed Ashiqur Rahman

Graduate Theses, Dissertations, and Problem Reports

Quantifying human biological age is an important and difficult challenge. Different biomarkers and numerous approaches have been studied for biological age prediction, each with its advantages and limitations. In this work, we first introduce a new anthropometric measure (called Surface-based Body Shape Index, SBSI) that accounts for both body shape and body size, and evaluate its performance as a predictor of all-cause mortality. We analyzed data from the National Health and Human Nutrition Examination Survey (NHANES). Based on the analysis, we introduce a new body shape index constructed from four important anthropometric determinants of body shape and body size: body ...


Real-Time Dengue Forecasting In Thailand: A Comparison Of Penalized Regression Approaches Using Internet Search Data, Caroline Kusiak 2018 University of Massachusetts Amherst

Real-Time Dengue Forecasting In Thailand: A Comparison Of Penalized Regression Approaches Using Internet Search Data, Caroline Kusiak

Masters Theses

Dengue fever affects over 390 million people annually worldwide and is of particu- lar concern in Southeast Asia where it is one of the leading causes of hospitalization. Modeling trends in dengue occurrence can provide valuable information to Public Health officials, however many challenges arise depending on the data available. In Thailand, reporting of dengue cases is often delayed by more than 6 weeks, and a small fraction of cases may not be reported until over 11 months after they occurred. This study shows that incorporating data on Google Search trends can improve dis- ease predictions in settings with severely ...


Modelling Heterogeneous Effects In Network Contagion: Evidence From The Steam Community, Henrique Laurino dos Santos 2018 University of Pennsylvania

Modelling Heterogeneous Effects In Network Contagion: Evidence From The Steam Community, Henrique Laurino Dos Santos

Wharton Research Scholars

This study considers heterogeneous effects of reviews and social interactions on diffusion or contagion of new products in a networked setting, using a sample of interconnected public user profiles from the Steam Community. Ownership and reviews of two cult hit independent games – The Binding of Isaac: Rebirth, and To the Moon – are analyzed over a period of four years. This data was fit with a Hawkes Process Hazard Regression Model with exponential decay kernels for each game, yielding estimates of scale and duration of incremental heterogeneous actions within the network. This analysis finds strong, short term, additive, and marginally decreasing ...


Survival Analysis: A Modified Kaplan-Meir Estimator, Justin A. Bancroft 2017 Missouri State University

Survival Analysis: A Modified Kaplan-Meir Estimator, Justin A. Bancroft

MSU Graduate Theses

The popular Kaplan-Meir estimator has traditionally been used to great effect as a survival function estimator. However, the Kaplan-Meir estimator is dependent upon a maximum likelihood parameter estimator which may not be the best estimator in all cases. We modify the Kaplan-Meir estimator, based on a Bayes parameter estimation, in hopes of providing a more accurate survival estimator for small sample sizes. Core elements of survival analysis are presented, acting as a foundation from which to construct and compare our modified Kaplan-Meir estimator. It is hypothesized that our modified Kaplan-Meir estimator is generally more accurate than the standard Kaplan-Meir estimator ...


On The Estimation Of Penetrance In The Presence Of Competing Risks With Family Data, Daniel Prawira 2017 The University of Western Ontario

On The Estimation Of Penetrance In The Presence Of Competing Risks With Family Data, Daniel Prawira

Electronic Thesis and Dissertation Repository

In family studies, we are interested in estimating the penetrance function of the event of interest in the presence of competing risks. Failure to account for competing risks may lead to bias in the estimation of the penetrance function. In this thesis, three statistical challenges are addressed: clustering, missing data, and competing risks. We proposed the cause-specific model with shared frailty and ascertainment correction to account for clustering and competing risks along with ascertainment of families into study. Multiple imputation is used to account for missing data. The simulation study showed good performance of our proposed model in estimating the ...


Statistical Methods For High Dimensional Data Arising From Large Epidemiological Studies, Hui Xu 2017 University of Massachusetts Amherst

Statistical Methods For High Dimensional Data Arising From Large Epidemiological Studies, Hui Xu

Doctoral Dissertations

In this thesis, we propose statistical models for addressing commonly encountered data types and study designs in large epidemiologic investigations aimed at understanding the molecular basis of complex disorders. The motivating applications come from diverse disease areas in Women's Health, including the study of type II diabetes in the Women's Health Initiative (WHI), invasive breast cancer in the Nurses' Health Study and the study of the metabolomic underpinnings of cardiovascular disease in the WHI. We have also put significant effort into making the implementation of the proposed methods accessible through freely available, user-friendly software packages in R.

The ...


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