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Full-Text Articles in Physical Sciences and Mathematics
Survival Analysis: An Exact Method For Rare Events, Kristina Reutzel
Survival Analysis: An Exact Method For Rare Events, Kristina Reutzel
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
Conventional asymptotic methods for survival analysis work well when sample sizes are at least moderately sufficient. When dealing with small sample sizes or rare events, the results from these methods have the potential to be inaccurate or misleading. To handle such data, an exact method is proposed and compared against two other methods: 1) the Cox proportional hazards model and 2) stratified logistic regression for discrete survival analysis data.
Multivariate Joint Models And Dynamic Predictions, Md Akhtar Hossain
Multivariate Joint Models And Dynamic Predictions, Md Akhtar Hossain
Theses and Dissertations
The joint modeling of longitudinal and time-to-event data is an active area of statistical research that has received a lot of attention. The standard joint models, referred to as univariate joint models, allow simultaneous modeling of a single longitudinal outcome and a single time-to-event under an assumption of independent censoring. The majority of the joint modeling research in the last two decades has focused on extending and improving the univariate joint models. While many of the practical applications involve data on multivariate longitudinal outcomes and multiple timeto- events possibly informatively censored by some other terminal time-to-event, the developments of joint …
Flexible Regression Models For Survival Data, Ennan Gu
Flexible Regression Models For Survival Data, Ennan Gu
Theses and Dissertations
Survival analysis is a branch of statistics to analyze the time-to-event data or survival data. One important feature of survival data is censoring, which means that not all the subjects’ survival time are observed directly. Among all the survival data, right-censored data are the most common type and consist of some exactly observed survival times and some right-censored observations. In this dissertation, we focus on studying flexible regression models for complicated right-censored survival data when the classical proportional hazards (PH) assumption is not satisfied. Flexible semiparametric regression models can largely avoid misspecification of parametric distributions and thus provide more modeling …
Gradient Boosting For Survival Analysis With Applications In Oncology, Nam Phuong Nguyen
Gradient Boosting For Survival Analysis With Applications In Oncology, Nam Phuong Nguyen
USF Tampa Graduate Theses and Dissertations
Cancer is one of the most deadly diseases that the world has been fighting against over decades. An enormous number of research has been conducted, via a wide scale of approaches, raging from genetic analysis to mathematical modeling. Survival analysis is a well-performed methodology frequently used to estimate the survival probability of a patient. Although there has been a large number of methods for survival analysis, efficient exploration of a high-dimensional feature space has been challenging due to its computational cost and complexity. This thesis adapts the component-wise gradient boosting algorithms for cancer survival analysis, and also proposes a new …
Parsimonious Covariate Selection For Interval Censored Data, Yi Cui
Parsimonious Covariate Selection For Interval Censored Data, Yi Cui
Legacy Theses & Dissertations (2009 - 2024)
Interval censored outcomes widely arise in many clinical trials and observational studies. In many cases, subjects are only followed-up periodically. As a result, the event of interest is known only to occur within a certain interval. We provided a method to select the parsimonious set of covariates associated with the interval censored outcome. First, the iterative sure independence screening (ISIS) method was applied to all interval censored time points across subjects to simultaneously select a set of potentially important covariates; then multiple testing approaches were used to improve the selection accuracy through refining the selection criteria, i.e. determining a refined …