Open Access. Powered by Scholars. Published by Universities.®
- Discipline
- Keyword
-
- Empirical Likelihood (3)
- AFT model (1)
- Average Causal Effect (1)
- Bayesian Adjustment for Confounding (1)
- Binary Choice Model (1)
-
- Clinical trial (1)
- Confidence Band (1)
- Covariate Adjustment (1)
- Cure rate (1)
- Delayed treatment effect (1)
- Detection limits (1)
- Environmental exposure (1)
- Hadamard Differentiable (1)
- Integrated weighted difference (1)
- Jackknife (1)
- Kernel smoothing (1)
- Left-censored data (1)
- Likelihood Ratio Test (1)
- Model Selection (1)
- Non-proportional hazards (1)
- Nonparametric estimator (1)
- Randomized Clinical Trial (1)
- Responder and non-responder (1)
- Sampling weight (1)
- Scaled Chi-Square (1)
- Statistical Functional (1)
- Survival Analysis (1)
- Weighted log-rank test (1)
Articles 1 - 6 of 6
Full-Text Articles in Survival Analysis
Innovative Statistical Models In Cancer Immunotherapy Trial Design, Jing Wei
Innovative Statistical Models In Cancer Immunotherapy Trial Design, Jing Wei
Theses and Dissertations--Statistics
A challenge arising in cancer immunotherapy trial design is the presence of non-proportional hazards (NPH) patterns in survival curves. We considered three different NPH patterns caused by delayed treatment effect, cure rate and responder rate of treatment group in this dissertation. These three NPH patterns would violate the proportional hazard model assumption and ignoring any of them in an immunotherapy trial design will result in substantial loss of statistical power.
In this dissertation, four models to deal with NPH patterns are discussed. First, a piecewise proportional hazards model is proposed to incorporate delayed treatment effect into the trial design consideration. …
Estimation Of The Treatment Effect With Bayesian Adjustment For Covariates, Li Xu
Estimation Of The Treatment Effect With Bayesian Adjustment For Covariates, Li Xu
Theses and Dissertations--Statistics
The Bayesian adjustment for confounding (BAC) is a Bayesian model averaging method to select and adjust for confounding factors when evaluating the average causal effect of an exposure on a certain outcome. We extend the BAC method to time-to-event outcomes. Specifically, the posterior distribution of the exposure effect on a time-to-event outcome is calculated as a weighted average of posterior distributions from a number of candidate proportional hazards models, weighing each model by its ability to adjust for confounding factors. The Bayesian Information Criterion based on the partial likelihood is used to compare different models and approximate the Bayes factor. …
Novel Computational Methods For Censored Data And Regression, Yifan Yang
Novel Computational Methods For Censored Data And Regression, Yifan Yang
Theses and Dissertations--Statistics
This dissertation can be divided into three topics. In the first topic, we derived a recursive algorithm for the constrained Kaplan-Meier estimator, which promotes the computation speed up to fifty times compared to the current method that uses EM algorithm. We also showed how this leads to the vast improvement of empirical likelihood analysis with right censored data. After a brief review of regularized regressions, we investigated the computational problems in the parametric/non-parametric hybrid accelerated failure time models and its regularization in a high dimensional setting. We also illustrated that, when the number of pieces increases, the discussed models are …
Empirical Likelihood And Differentiable Functionals, Zhiyuan Shen
Empirical Likelihood And Differentiable Functionals, Zhiyuan Shen
Theses and Dissertations--Statistics
Empirical likelihood (EL) is a recently developed nonparametric method of statistical inference. It has been shown by Owen (1988,1990) and many others that empirical likelihood ratio (ELR) method can be used to produce nice confidence intervals or regions. Owen (1988) shows that -2logELR converges to a chi-square distribution with one degree of freedom subject to a linear statistical functional in terms of distribution functions. However, a generalization of Owen's result to the right censored data setting is difficult since no explicit maximization can be obtained under constraint in terms of distribution functions. Pan and Zhou (2002), instead, study the …
Statistical Methods For Environmental Exposure Data Subject To Detection Limits, Yuchen Yang
Statistical Methods For Environmental Exposure Data Subject To Detection Limits, Yuchen Yang
Theses and Dissertations--Statistics
In this dissertation, we develop unified and efficient nonparametric statistical methods for estimating and comparing environmental exposure distributions in presence of detection limits. In the first part, we propose a kernel-smoothed nonparametric estimator for the exposure distribution without imposing any independence assumption between the exposure level and detection limit. We show that the proposed estimator is consistent and asymptotically normal. Simulation studies demonstrate that the proposed estimator performs well in practical situations. A colon cancer study is provided for illustration. In the second part, we develop a class of test statistics to compare exposure distributions between two groups by using …
Empirical Likelihood Confidence Band, Shihong Zhu
Empirical Likelihood Confidence Band, Shihong Zhu
Theses and Dissertations--Statistics
The confidence band represents an important measure of uncertainty associated with a functional estimator and empirical likelihood method has been proved to be a viable approach to constructing confidence bands in many cases. Using the empirical likelihood ratio principle, this dissertation developed simultaneous confidence bands for many functions of fundamental importance in survival analysis, including the survival function, the difference and ratio of survival functions, the hazards ratio function, and other parameters involving residual lifetimes. Covariate adjustment was incorporated under the proportional hazards assumption. The proposed method can be very useful when, for example, an individualized survival function is desired …