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Full-Text Articles in Physical Sciences and Mathematics
Hypothesis Testing For An Extended Cox Model With Time-Varying Coefficients, Takumi Saegusa, Chongzhi Di, Ying Qing Chen
Hypothesis Testing For An Extended Cox Model With Time-Varying Coefficients, Takumi Saegusa, Chongzhi Di, Ying Qing Chen
UW Biostatistics Working Paper Series
The log-rank test has been widely used to test a treatment effect under the Cox model for censored time-to-event outcomes, though it may lose power substantially when the model's proportional hazards assumption does not hold. In this paper, we consider an extended Cox model that uses B-splines or smoothing splines to model a time-varying treatment effect and propose score test statistics for the treatment effect. Our proposed new tests combine statistical evidence from both the magnitude and the shape of the time-varying hazard ratio function, and thus are omnibus and powerful against various types of alternatives. In addition, the new …
Business Failure Prediction Using Statistical Techniques: A Review, Adrian Gepp, Kuldeep Kumar
Business Failure Prediction Using Statistical Techniques: A Review, Adrian Gepp, Kuldeep Kumar
Adrian Gepp
Accurate business failure prediction models would be extremely valuable to many industry sectors, particularly in financial investment and lending. The potential value of such models has been recently emphasised by the extremely cosdy failure of high profile businesses in both Australia and overseas, such as HIH (Australia) and Enron (USA). Consequently, there has been a significant increase in interest in business failure prediction from both industry and academia. Statistical business failure prediction models attempt to predict the failure or success of a business. Discriminant and logit analyses are the most popular approaches, and there are also a large number of …
Penalized Smoothed Partial Rank Estimator For The Nonparametric Transformation Survival Model With High-Dimensional Covariates, Wei Dai, Yi Li
Penalized Smoothed Partial Rank Estimator For The Nonparametric Transformation Survival Model With High-Dimensional Covariates, Wei Dai, Yi Li
The University of Michigan Department of Biostatistics Working Paper Series
Microarray technology has the potential to lead to a better understanding of biological processes and diseases such as cancer. When failure time outcomes are also available, one might be interested in relating gene expression profiles to the survival outcome such as time to cancer recurrence or time to death. This is statistically challenging because the number of covariates greatly exceeds the number of observations. While the majority of work has focused on regularized Cox regression model and accelerated failure time model, they may be restrictive in practice. We relax the model assumption and and consider a nonparametric transformation model that …
A Frailty Approach For Survival Analysis With Error-Prone Covariate, Sehee Kim, Yi Li, Donna Spiegelman
A Frailty Approach For Survival Analysis With Error-Prone Covariate, Sehee Kim, Yi Li, Donna Spiegelman
The University of Michigan Department of Biostatistics Working Paper Series
This paper discovers an inherent relationship between the survival model with covariate measurement error and the frailty model. The discovery motivates our using a frailty-based estimating equation to draw inference for the proportional hazards model with error-prone covariates. Our established framework accommodates general distributional structures for the error-prone covariates, not restricted to a linear additive measurement error model or Gaussian measurement error. When the conditional distribution of the frailty given the surrogate is unknown, it is estimated through a semiparametric copula function. The proposed copula-based approach enables us to fit flexible measurement error models without the curse of dimensionality as …
Non-Likelihood Based Model Evaluation And Comparison With Application To Genetic And Clinical Hiv-1 Outcomes, Ashley Elise Giambrone
Non-Likelihood Based Model Evaluation And Comparison With Application To Genetic And Clinical Hiv-1 Outcomes, Ashley Elise Giambrone
Legacy Theses & Dissertations (2009 - 2024)
Although treatment for human immunodeficiency virus type-1 (HIV-1) has undergone drastic change and morbidity and mortality has decreased over time, the development of drug-resistant HIV-1 is of concern for the long-term antiretroviral treatment of infected individuals. Drug-resistant virus is known to manifest with potentially complex mutational patterns in the HIV-1 genotype sequence and is associated with decreased response to therapy. Resistance occurs either as a result of development of mutations in the viral genome under selective drug pressure or as a result of naturally occurring polymorphisms. The most effective treatment methods are still debated at this time; however, current treatment …
A Monte Carlo Approach To Change Point Detection In A Liver Transplant, Alexia Melissa Makris
A Monte Carlo Approach To Change Point Detection In A Liver Transplant, Alexia Melissa Makris
USF Tampa Graduate Theses and Dissertations
Patient survival post liver transplant (LT) is important to both the patient and the center's accreditation, but over the years physicians have noticed that distant patients struggle with post LT care. I hypothesized that patient's distance from the transplant center had a detrimental effect on post LT survival. I suspected Hepatitis C (HCV) and Hepatocellular Carcinoma (HCC) patients would deteriorate due to their recurrent disease and there is a need for close monitoring post LT. From the current literature it was not clear if patients' distance from a transplant center affects outcomes post LT. Firozvi et al. (Firozvi AA, 2008) …