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Full-Text Articles in Physical Sciences and Mathematics
Bayesian Phase I Dose Finding In Cancer Trials, Lin Yang
Bayesian Phase I Dose Finding In Cancer Trials, Lin Yang
Dissertations & Theses (Open Access)
This dissertation explores phase I dose-finding designs in cancer trials from three perspectives: the alternative Bayesian dose-escalation rules, a design based on a time-to-dose-limiting toxicity (DLT) model, and a design based on a discrete-time multi-state (DTMS) model.
We list alternative Bayesian dose-escalation rules and perform a simulation study for the intra-rule and inter-rule comparisons based on two statistical models to identify the most appropriate rule under certain scenarios. We provide evidence that all the Bayesian rules outperform the traditional ``3+3'' design in the allocation of patients and selection of the maximum tolerated dose.
The design based on a time-to-DLT model …
Statistical Analysis Of Fatalities Due To Vehicle Accidents In Las Vegas, Nv, Annabelle Marie Mathis
Statistical Analysis Of Fatalities Due To Vehicle Accidents In Las Vegas, Nv, Annabelle Marie Mathis
UNLV Theses, Dissertations, Professional Papers, and Capstones
The goal of this thesis is to investigate factors that affect the odds of having a fatality in a vehicle collision. We will be looking at characteristics of the driver that caused the accident (age, gender, behavior, actions, influences, and seat belt worn), the characteristics of the vehicle the driver drove (type of vehicle, and air bag deployment), the characteristics of the environment in which the accident occurred (weather, road condition, lighting, time of day, the day of the week, and month of the year), the characteristics of the crash (direction of accident and how many vehicles were involved), and …
Bayesian Semiparametric Generalizations Of Linear Models Using Polya Trees, Angela Schoergendorfer
Bayesian Semiparametric Generalizations Of Linear Models Using Polya Trees, Angela Schoergendorfer
University of Kentucky Doctoral Dissertations
In a Bayesian framework, prior distributions on a space of nonparametric continuous distributions may be defined using Polya trees. This dissertation addresses statistical problems for which the Polya tree idea can be utilized to provide efficient and practical methodological solutions.
One problem considered is the estimation of risks, odds ratios, or other similar measures that are derived by specifying a threshold for an observed continuous variable. It has been previously shown that fitting a linear model to the continuous outcome under the assumption of a logistic error distribution leads to more efficient odds ratio estimates. We will show that deviations …