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Empirical Likelihood Ratio Tests For Homogeneity Of Distributions Of Component Lifetimes From System Lifetime Data With Known System Structures, Jingjing Qu 2023 Southern Methodist University

Empirical Likelihood Ratio Tests For Homogeneity Of Distributions Of Component Lifetimes From System Lifetime Data With Known System Structures, Jingjing Qu

Statistical Science Theses and Dissertations

In system reliability, practitioners may be interested in testing the homogeneity of the component lifetime distributions based on system lifetimes from multiple data sources for various reasons, such as identifying the component supplier that provides the most reliable components.

In the first part of the dissertation, we develop distribution-free hypothesis testing procedures for the homogeneity of the component lifetime distributions based on system lifetime data when the system structures are known. Several nonparametric testing statistics based on the empirical likelihood method are proposed for testing the homogeneity of two or more component lifetime distributions. The computational approaches to obtain the …


An Analysis Of All-Cause Mortality On Patients With Sickle Cell Disease And Kidney Disease Using Propensity Score Matching, Adam Garrison 2023 Stephen F. Austin State University

An Analysis Of All-Cause Mortality On Patients With Sickle Cell Disease And Kidney Disease Using Propensity Score Matching, Adam Garrison

Electronic Theses and Dissertations

In this work, we provide an overview of the Cox proportional hazards model for time to event or survival analysis and the notion of propensity score matching to deal with confounding factors. A full analysis is reported in Chapter 2 concerning mortality for in-center dialysis patients with sickle cell disease to demonstrate the application of a general analysis strategy that has some logistical benefits over more traditional approaches to accounting for confounding variables. We also provide some insight and discussions on the challenges and future research questions that will emerge when trying to implement this strategy as a monitoring tool …


A New Generalized Gamma-Weibull Distribution And Its Applications, Nihimat Iyebuhola Aleshinloye, Samuel Adewale Aderoju, Alfred Adewole Abiodun, Bako Lukmon Taiwo 2023 Department of Mathematics and Statistics, Kwara State University, Malete P.M.B. 1530, Ilorin, Nigeria

A New Generalized Gamma-Weibull Distribution And Its Applications, Nihimat Iyebuhola Aleshinloye, Samuel Adewale Aderoju, Alfred Adewole Abiodun, Bako Lukmon Taiwo

Al-Bahir

In this paper, a New Generalized Gamma-Weibull (NGGW) distribution is developed by compounding Weibull and generalized gamma distribution. Some mathematical properties such as moments, Rényi entropy and order statistics are derived and discussed. The maximum likelihood estimation (MLE) method is used to estimate the model parameters. The proposed model is applied to two real-life datasets to illustrate its performance and flexibility as compared to some other competing distributions. The results obtained show that the new distribution fits each of the data better than the other competing distributions.


Examining Fuel Service System Failures Of The Usaf R11 Using Survival Analysis, Roed M.S. Mejia 2023 Air Force Institute of Technology

Examining Fuel Service System Failures Of The Usaf R11 Using Survival Analysis, Roed M.S. Mejia

Theses and Dissertations

Recent events show that fuel supply is a large contributor to the success or failure of a military operation in response to a contingency. Any future near-peer conflict will stress the supply chain and require fully operational vehicles to be ready for the primary mission sets they support. In the United States Air Force (USAF), the readiness of fuel distribution trucks is crucial to meeting those mission sets in global operations. Utilizing non-parametric and semi-parametric survival models, which do not assume specific probability distributions, this study analyzes maintenance data for R-11 trucks that refuel aircraft.


Examining Failures Of Kc-135 Boom Assemblies Using Survival Analysis, Benjamin D. Miller 2023 Air Force Institute of Technology

Examining Failures Of Kc-135 Boom Assemblies Using Survival Analysis, Benjamin D. Miller

Theses and Dissertations

The purposes of this study are to confirm the applicability of survival analysis for predicting recurrent failures of a component of a military aircraft and to provide practical insights to maintenance managers and mission planners. The results of this study also can help the United States Department of Defense improve the CBM+ program. This study was able to predict recurrent failures of the component using Nelson-Aalen cumulative estimates. In addition, this study used a Cox proportional hazards regression model with shared frailty for measuring the effect of covariates on recurrent failures and unidentified heterogeneity in the model, which warranted future …


Debris Survivability Study For Mega-Constellation Architectures, Joseph C. Canoy 2023 Air Force Institute of Technology

Debris Survivability Study For Mega-Constellation Architectures, Joseph C. Canoy

Theses and Dissertations

The analysis for the overall theoretical debris survivabilty of mega-constellation architectures, with an emphasis on space-based ballistic missile defense constellation (SB-BMD), is explored via three extensive different Monte Carlo simulations: preliminary analysis of low Earth Orbit (LEO) mega-constellation survivabilty following a fragmentation event within the constellation, analysis of LEO mega-constellation survivability with a fragmentation event occurring on a satellite performing a maneuver to insert itself within the constellation, and the analysis of LEO mega-constellation survivabilty after a fragmentation event resulting from the destruction of a missile. The LEO mega-constellations represent the SB-BMD constellation. The first two analysis sections will include …


Forecasting Remission Time Of A Treatment Method For Leukemia As An Application To Statistical Inference Approach, Ahmed Galal Atia, Mahmoud Mansour, Rashad Mohamed El-Sagheer, B. S. El-Desouky 2023 Mansoura University

Forecasting Remission Time Of A Treatment Method For Leukemia As An Application To Statistical Inference Approach, Ahmed Galal Atia, Mahmoud Mansour, Rashad Mohamed El-Sagheer, B. S. El-Desouky

Basic Science Engineering

In this paper, Weibull-Linear Exponential distribution (WLED) has been investigated whether being it is a well-fit distribution to a clinical real data. These data represent the duration of remission achieved by a certain drug used in the treatment of leukemia for a group of patients. The statistical inference approach is used to estimate the parameters of the WLED through the set of the fitted data. The estimated parameters are utilized to evaluate the survival and hazard functions and hence assessing the treatment method through forecasting the duration of remission times of patients. A two-sample prediction approach has been applied to …


Striving For Appropriate Antibiotic Use: A Biomarker Initiative, And Outcomes Associated With Azithromycin Exposure, Amanda Gusovsky 2023 University of Kentucky

Striving For Appropriate Antibiotic Use: A Biomarker Initiative, And Outcomes Associated With Azithromycin Exposure, Amanda Gusovsky

Theses and Dissertations--Pharmacy

The introduction of antibiotics into clinical practice is considered the greatest medical breakthrough of the 20thcentury. However, the use of antibiotics can contribute to the development of resistance. In the United States (U.S.), approximately 2.8 million people are infected with antibiotic-resistant bacteria each year, and more than 35,000 people die as a result. Moreover, some antibiotics are known to cause cardiac side effects including QT prolongation, hypotension, and ventricular arrythmias. The U.S. Centers for Disease Control and Prevention (CDC) defines appropriate antibiotic use as the effort to use “the right antibiotic, at the right dose, for the right …


Novel Feature Evaluation In Ultra-High Dimensional Right-Censored Data, With Applications To Head And Neck Cancer, Atika Farzana Urmi 2023 Virginia Commonwealth University

Novel Feature Evaluation In Ultra-High Dimensional Right-Censored Data, With Applications To Head And Neck Cancer, Atika Farzana Urmi

Graduate Research Posters

Background: Head and neck cancer is the 6th most common cancer worldwide with an expected 1.08 million new cases each year. Such cancer data are ultra-high dimensional with thousands of clinical features and gene expressions, making it challenging for the traditional analytical tools to extract the potential biomarker for the cancer survival and control false discoveries. In addition, presence of heavy censoring can affect the screening procedures based on Kaplan-Meier (K-M) survival estimates.

Aim: To propose a model free, ultra-high dimensional feature screening method with two-dimensional survival outcome allowing false discovery rate (FDR) control.

Method: 516 primary tumor patients with …


Regression Modeling Of Complex Survival Data Based On Pseudo-Observations, Rong Rong 2022 Southern Methodist University

Regression Modeling Of Complex Survival Data Based On Pseudo-Observations, Rong Rong

Statistical Science Theses and Dissertations

The restricted mean survival time (RMST) is a clinically meaningful summary measure in studies with survival outcomes. Statistical methods have been developed for regression analysis of RMST to investigate impacts of covariates on RMST, which is a useful alternative to the Cox regression analysis. However, existing methods for regression modeling of RMST are not applicable to left-truncated right-censored data that arise frequently in prevalent cohort studies, for which the sampling bias due to left truncation and informative censoring induced by the prevalent sampling scheme must be properly addressed. Meanwhile, statistical methods have been developed for regression modeling of the cumulative …


Infrastructure Development For Personalized Risk Prediction To Reduce Cardiovascular Disease In Childhood Cancer Survivors, Suman Shrestha 2022 The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences

Infrastructure Development For Personalized Risk Prediction To Reduce Cardiovascular Disease In Childhood Cancer Survivors, Suman Shrestha

Dissertations and Theses (Open Access)

Although childhood cancer survivors have lengthy life expectancies, they run the risk of experiencing long-term health issues as a result of their treatment. The most frequent non-cancerous cause of morbidity and mortality for these survivors is cardiac disease. Radiation therapy (RT) has been linked in numerous cohort studies to a higher chance of developing a late cardiac disease in these survivors, and this risk rises with higher mean heart doses and increased RT exposure to larger cardiac volumes. Since, the heart is a heterogeneous organ made up of several distinct substructures, RT dose received by the entire heart does not …


Hypothesis Testing And Parameter Estimation In Mixture Cure Models For Cancer Survival Data, Mohammod Mahmudur Rahman 2022 University of Arkansas, Fayetteville

Hypothesis Testing And Parameter Estimation In Mixture Cure Models For Cancer Survival Data, Mohammod Mahmudur Rahman

Graduate Theses and Dissertations

In oncology clinical trials, when a treatment is administered to the patient population, a certain subset of patients may respond to the treatment while the other does not. The positive responders with long-term survival are considered “statistically cured” and can be referred to as cured patients or long-term survivors. When a proportion of patients achieve long-term survival, the hazard functions of two arms (control vs. treatment) are no longer proportional. As a result, the traditional log-rank test, which is the most popular test to evaluate the effectiveness of a treatment in clinical trials, tends to lose its power. In this …


Dynamic Prediction For Alternating Recurrent Events Using A Semiparametric Joint Frailty Model, Jaehyeon Yun 2022 Southern Methodist University

Dynamic Prediction For Alternating Recurrent Events Using A Semiparametric Joint Frailty Model, Jaehyeon Yun

Statistical Science Theses and Dissertations

Alternating recurrent events data arise commonly in health research; examples include hospital admissions and discharges of diabetes patients; exacerbations and remissions of chronic bronchitis; and quitting and restarting smoking. Recent work has involved formulating and estimating joint models for the recurrent event times considering non-negligible event durations. However, prediction models for transition between recurrent events are lacking. We consider the development and evaluation of methods for predicting future events within these models. Specifically, we propose a tool for dynamically predicting transition between alternating recurrent events in real time. Under a flexible joint frailty model, we derive the predictive probability of …


Statistical Methods For Personalized Treatment Selection And Survival Data Analysis Based On Observational Data With High-Dimensional Covariates., Don Ramesh Dinendra Sudaraka Tholkage 2022 University of Louisville

Statistical Methods For Personalized Treatment Selection And Survival Data Analysis Based On Observational Data With High-Dimensional Covariates., Don Ramesh Dinendra Sudaraka Tholkage

Electronic Theses and Dissertations

Due to the wide availability of functional data from multiple disciplines, the studies of functional data analysis have become popular in the recent literature. However, the related development in censored survival data has been relatively sparse. In Chapter 2, we consider the problem of analyzing time-to-event data in the presence of functional predictors. We develop a conditional generalized Kaplan Meier (KM) estimator that incorporates functional predictors using kernel weights and rigorously establishes its asymptotic properties. In addition, we propose to select the optimal bandwidth based on a time-dependent Brier score. We then carry out extensive numerical studies to examine the …


Statistical Modeling Of Longitudinal Medical Cost Data, Shikun Wang 2022 The Texas Medical Center Library

Statistical Modeling Of Longitudinal Medical Cost Data, Shikun Wang

Dissertations and Theses (Open Access)

Projecting the future cancer care cost is critical in health economics research and policy making. An indispensable step is to estimate cost trajectories from an incident cohort of cancer patients using longitudinal medical cost data, accounting for terminal events such as death, and right censoring due to loss of follow-up. Since the cost of cancer care and survival are correlated, a scientifically meaningful quantity for inference in this context is the mean cost trajectory conditional on survival. Many standard approaches for longitudinal and survival analysis are not valid for the problem. The research for my Ph.D. dissertation consists of three …


Effect Of Monetary Policy Rate On Market Interest Rates In Nigeria: A Threshold And Nardl Approach, Oluwafemi E. Awopegba, Joseph O. Afolabi, Lydia T. Adeoye, Godwin O. Akpokodje 2022 Nigerian Institute of Social and Economic Research (NISER)

Effect Of Monetary Policy Rate On Market Interest Rates In Nigeria: A Threshold And Nardl Approach, Oluwafemi E. Awopegba, Joseph O. Afolabi, Lydia T. Adeoye, Godwin O. Akpokodje

CBN Journal of Applied Statistics (JAS)

This study examines the effect of monetary policy rate (MPR) on market interest rates in Nigeria. For parsimony, we develop two indexes called the short-term interest rate (SINT) and Lending interest rate (LINT) to represent deposit and lending rates respectively. The nonlinear autoregressive distributed lag (NARDL) and threshold regression models are adopted. The study uses monthly data from 2002:M1 to 2019:M12. The results of the threshold regression model indicate that the degree of the effect of MPR on SINT and LINT above the estimated threshold of 11 and 13 percent respectively is greater and significant than if MPR were to …


Social Dimension Of Inclusive Growth In Ecowas: Implication For Poverty Reduction, Toriola K. Anu, Goerge O. Emmanuel, Ajayi O. Felix 2022 : Department of Economics, Olabisi Onabanjo University, Ago-Iwoye, Nigeria.

Social Dimension Of Inclusive Growth In Ecowas: Implication For Poverty Reduction, Toriola K. Anu, Goerge O. Emmanuel, Ajayi O. Felix

CBN Journal of Applied Statistics (JAS)

This study investigates the implication of the social dimension of inclusive growth on poverty reduction in Economic Community of West African States (ECOWAS) countries. It specifically examines how social indices of inclusive growth comprising of income inequality, education, and health outcomes affect poverty reduction. The study uses a panel dataset of the six (6) lower-middle income countries in ECOWAS which was analysed via panel Difference Generalised Method of Moment (D-GMM). The results show that GDP per capita exerts significant negative effect on poverty while inequality, education and health outcomes do not show significant effect on poverty. Although, the estimates of …


Effect Of Fdi Inflows On Employment Generation In Selected Ecowas Countries: Heterogeneous Panel Analysis, Timothy A. Aderemi, Olawunmi Omitogun, Bukonla G. Osisanwo 2022 Central Bank of Nigeria

Effect Of Fdi Inflows On Employment Generation In Selected Ecowas Countries: Heterogeneous Panel Analysis, Timothy A. Aderemi, Olawunmi Omitogun, Bukonla G. Osisanwo

CBN Journal of Applied Statistics (JAS)

The aim of this study is to examine the effect of FDI on employment in ECOWAS sub region between 1990 and 2019. The study utilizes a panel autoregressive distributed lag model to analyse the short run and long run relationship between FDI and employment across ECOWAS sub region. In the short run, the impact of FDI on employment is negative and statistically not significant. Meanwhile, in the long run FDI has a positive and statistically significant impact on employment rate. This implies that FDI has the capacity to generate employment in countries in ECOWAS sub region. Therefore, this study recommends …


Impact Of Covid-19 Pandemic On The Nigeria Stock Market: A Sectoral Stock Prices Analysis, Peter A. Adekunle, Yakubu A. Bello, Udochukwu G. Nwachukwu 2022 Central Bank of Nigeria

Impact Of Covid-19 Pandemic On The Nigeria Stock Market: A Sectoral Stock Prices Analysis, Peter A. Adekunle, Yakubu A. Bello, Udochukwu G. Nwachukwu

CBN Journal of Applied Statistics (JAS)

This study examines the impact of the COVID-19 pandemic on sectoral stock prices in Nigeria stock market using daily data covering from February 28, 2020 to June 26, 2020. Applying the autoregressive distributed lag (ARDL) bounds test, the study finds that COVID-19 pandemic had adverse impact on the stock market indices in the short run. Furthermore, the study documents negative response of sectoral stock prices to the pandemic while the stock prices of the banking sub-sector are the worst hit. Compared to the consumer goods, and industrial subsector indices, the speed of adjustment to long run equilibrium is faster for …


Factors Affecting Time To Recovery: A Covid-19 Survival Analysis, Fernanda Montoya 2022 Northern Illinois University

Factors Affecting Time To Recovery: A Covid-19 Survival Analysis, Fernanda Montoya

Honors Capstones

This project is focused on the recovery rates of patients diagnosed with COVID-19 after different clinical trial drug treatments. Data for the clinical trial studied was obtained from the National Institute of Allergy and Infectious Diseases for the primary purpose of a survival analysis on patient time to recovery under a placebo and therapeutic drug treatment. Specifically, patients in this clinical trial were randomly selected to receive remdesivir, an antiviral drug, in combination with a placebo or baricitinib, a janus kinase inhibitor drug. Cox PH models were used to identify how the different treatment drugs affect time to recovery and …


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