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Articles 1 - 8 of 8
Full-Text Articles in Physical Sciences and Mathematics
Simulation Based Evaluation Of Multiscale Small Area Health Models, Purbasha Dasgupta
Simulation Based Evaluation Of Multiscale Small Area Health Models, Purbasha Dasgupta
Theses and Dissertations
The effects of scale on the analysis of spatial data, often referred to as the modifiable areal unit problem in spatial studies, is one of the issues often encountered in small area health models. These spatial effects of scale are also seen in the areas of disease mapping where data are usually available in counts. Often there is a need to consider the different scales of aggregation that exist within count data, since inferences based on analyses can vary if we change the definition of the unit of analysis. This thesis provides a framework that describes the distribution of relative …
Methods For Identifying Regions Of Brain Activation Using Fmri Meta-Data, Meredith A. Ray
Methods For Identifying Regions Of Brain Activation Using Fmri Meta-Data, Meredith A. Ray
Theses and Dissertations
Functional neuroimaging is a relatively young discipline within the neurosciences that has led to significant advances in our understanding of the human brain and progress in neuroscientific research related to public health. Accurately identifying activated regions in the brain showing a strong association with an outcome of interest is crucial in terms of disease prediction and prevention. Functional magnetic resonance imaging (fMRI) is the most widely used method for this type of study as it has the ability to measure and identify the location of changes in tissue perfusion, blood oxygenation, and blood volume. In practice, the three-dimensional brain locations …
Semiparametric Regression Analysis Of Bivariate Interval-Censored Data, Naichen Wang
Semiparametric Regression Analysis Of Bivariate Interval-Censored Data, Naichen Wang
Theses and Dissertations
Survival analysis is a long-lasting and popular research area and has numerous applications in all fields such as social science, engineering, economics, industry, and public health. Interval-censored data are a special type of survival data, in which the survival time of interest is never exactly observed but is known to fall within some observed interval. Interval-censored data arise commonly in real-life studies, in which subjects are examined at periodical or irregular follow-up visits. In this dissertation, we develop efficient statistical approaches for regression analysis of bivariate intervalcensored data, in which the two survival times of interest are correlated and both …
Non- And Semi-Parametric Bayesian Inference With Recurrent Events And Coherent Systems Data, A. K. M. Fazlur Rahman
Non- And Semi-Parametric Bayesian Inference With Recurrent Events And Coherent Systems Data, A. K. M. Fazlur Rahman
Theses and Dissertations
This dissertation deals with non- and semi-parametric Bayesian inference of gap-time distribution with recurrent event data and simultaneous inference of component and system reliabilities of coherent systems data. Recurrent event data arise from a wide variety of studies/fields such as clinical trials, epidemiology, public health, biomedicine (e.g. repeated heart attack, repeated tumor occurrences of a cancer patient). In Chapter 2 we develop nonparametric Bayes and empirical Bayes estimators of the survivor function \bar{F} = 1 - F, of the gap-time distribution by assigning a Dirichlet process prior on F. We develop a closed form estimator of \bar{F} as well as …
Bayesian Analysis Of Continuous Curve Functions, Wen Cheng
Bayesian Analysis Of Continuous Curve Functions, Wen Cheng
Theses and Dissertations
We consider Bayesian analysis of continuous curve functions in 1D, 2D and 3D spaces. A fundamental feature of the analysis is that it is invariant under a simultaneous warping/re-parameterization of all target curves, as well as translation, rotation and scale of each individual if necessary. We introduce Bayesian models based on a special curve representation named Square Root Velocity Function (SRVF) introduced by Srivastava et al. (2011, IEEE PAMI). A Gaussian process model for the SRVFs of curves is proposed, and suitable prior models such as the Dirichlet distribution are employed for modeling the warping function as a cumulative distribution …
Methods For Clustering Mixed Data, Jeanmarie L. Hendrickson
Methods For Clustering Mixed Data, Jeanmarie L. Hendrickson
Theses and Dissertations
We give a brief introduction to cluster analysis and then propose and discuss a few methods for clustering mixed data. In particular, a model-based clustering method for mixed data based on Everitt's (1988) work is described, and we use a simulated annealing method to estimate the parameters for Everitt's model. A penalized log likelihood with the simulated annealing method is proposed as a remedy for the parameter estimates being drawn to extremes. Everitt's approach and the proposed method are compared based on their performance in clustering simulated data. We then use the penalized log likelihood method on a heart disease …
Applications Of Bayesian Nonparametrics To Reliability And Survival Data, Li Li
Applications Of Bayesian Nonparametrics To Reliability And Survival Data, Li Li
Theses and Dissertations
Reliability and survival data are widely encountered across many common settings. Subjects under investigation often include machines, bioassays, patients, etc.; their reliability or survival distribution, and its association with covariate processes, are commonly of interest. Within this dissertation, the first two chapters focus on reliability data where repairable systems fail and get interventions, e.g. repairs in the event process. It begins with a nonparametric test for the commonly assumed ''good as old'' assumption for minimal repair models and then a semi-parametric regression model is introduced for reliability data using Kijima's effective age. The third chapter focuses on survival data observed …
Oldtimers & Newcomers In Collective Action, Stefanie R. Chamberlain
Oldtimers & Newcomers In Collective Action, Stefanie R. Chamberlain
Theses and Dissertations
Most work on groups facing collective action assumes that group membership is static, or fixed. Yet static membership is rare, with members joining and leaving groups. In this thesis, I propose to explore how the presence of newcomers to groups affects group coordination. Past research has shown an overall negative effect of newcomers on group contributions. The proposed thesis attempts to further establish the effect by determining whether newcomers, oldtimers, or both are responsible for the declining cooperation in groups. While the empirical component is focused solely on establishing who is responsible for driving down cooperation rates in dynamic groups, …