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Articles 1 - 4 of 4
Full-Text Articles in Survival Analysis
Hypothesis Testing And Parameter Estimation In Mixture Cure Models For Cancer Survival Data, Mohammod Mahmudur Rahman
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 …
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 …
Asymptotic Results For Simultaneous Group Sequential Analysis Of Rank-Based And Weighted Kaplan-Meier Tests With Paired Survival Data In The Presence Of Censoring. Technical Report, Adin-Cristian Andrei, Susan Murray
Asymptotic Results For Simultaneous Group Sequential Analysis Of Rank-Based And Weighted Kaplan-Meier Tests With Paired Survival Data In The Presence Of Censoring. Technical Report, Adin-Cristian Andrei, Susan Murray
The University of Michigan Department of Biostatistics Working Paper Series
This research sequentially monitors paired survival differences using a new class of non-parametric tests based on functionals of standardized paired weighted log-rank (PWLR) and standardized paired weighted Kaplan-Meier (PWKM) tests. During a trial these tests may alternately assume the role of the more extreme statistic. By monitoring PEMAX, the maximum between the absolute values of the standardized PWLR and PWKM, one combines advantages of rank-based and non rank-based paired testing paradigms. Simulations show that monitoring treatment differences using PEMAX maintains type I error and is nearly as powerful as using the more advantageous of the two tests, in proportional hazards …
A Class Of Semiparametric Scale-Change Hazards Regression Models And Its Adequacy For Censored Survival Data, Ying Qing Chen
A Class Of Semiparametric Scale-Change Hazards Regression Models And Its Adequacy For Censored Survival Data, Ying Qing Chen
U.C. Berkeley Division of Biostatistics Working Paper Series
A class of semiparametric hazards regression models called the accelerated hazards models was introduced to identify the covariate effect characterized by the scale-change between hazard functions. In this article, we compare the accelerated hazards models with several other popular classes of regression models in statistical literature for censored survival data. We also propose and study some test statistics to assess the models' adequacy. Simulation studies are conducted to evaluate the performance of the test statistics. Actual clinical trials data are analyzed to demonstrate the proposed models and test statistics.