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Full-Text Articles in Physical Sciences and Mathematics

Thinking Outside The Curve, Part Ii: Modeling Fetal-Infant Mortality, Richard Charnigo, Lorie W. Chesnut, Tony Lobianco, Russell S. Kirby Aug 2010

Thinking Outside The Curve, Part Ii: Modeling Fetal-Infant Mortality, Richard Charnigo, Lorie W. Chesnut, Tony Lobianco, Russell S. Kirby

Statistics Faculty Publications

BACKGROUND: Greater epidemiologic understanding of the relationships among fetal-infant mortality and its prognostic factors, including birthweight, could have vast public health implications. A key step toward that understanding is a realistic and tractable framework for analyzing birthweight distributions and fetal-infant mortality. The present paper is the second of a two-part series that introduces such a framework.

METHODS: We propose estimating birthweight-specific mortality within each component of a normal mixture model representing a birthweight distribution, the number of components having been determined from the data rather than fixed a priori.

RESULTS: We address a number of methodological issues related to our …


Thinking Outside The Curve, Part I: Modeling Birthweight Distribution, Richard Charnigo, Lorie W. Chesnut, Tony Lobianco, Russell S. Kirby Jul 2010

Thinking Outside The Curve, Part I: Modeling Birthweight Distribution, Richard Charnigo, Lorie W. Chesnut, Tony Lobianco, Russell S. Kirby

Statistics Faculty Publications

BACKGROUND: Greater epidemiologic understanding of the relationships among fetal-infant mortality and its prognostic factors, including birthweight, could have vast public health implications. A key step toward that understanding is a realistic and tractable framework for analyzing birthweight distributions and fetal-infant mortality. The present paper is the first of a two-part series that introduces such a framework.

METHODS: We propose describing a birthweight distribution via a normal mixture model in which the number of components is determined from the data using a model selection criterion rather than fixed a priori.

RESULTS: We address a number of methodological issues, including how the …


A Markov Transition Model To Dementia With Death As A Competing Event, Liou Xu Jan 2010

A Markov Transition Model To Dementia With Death As A Competing Event, Liou Xu

University of Kentucky Doctoral Dissertations

The research on multi-state Markov transition model is motivated by the nature of the longitudinal data from the Nun Study (Snowdon, 1997), and similar information on the BRAiNS cohort (Salazar, 2004). Our goal is to develop a flexible methodology for handling the categorical longitudinal responses and competing risks time-to-event that characterizes the features of the data for research on dementia. To do so, we treat the survival from death as a continuous variable rather than defining death as a competing absorbing state to dementia. We assume that within each subject the survival component and the Markov process are linked by …


Comparison Of Two Samples By A Nonparametric Likelihood-Ratio Test, William H. Barton Jan 2010

Comparison Of Two Samples By A Nonparametric Likelihood-Ratio Test, William H. Barton

University of Kentucky Doctoral Dissertations

In this dissertation we present a novel computational method, as well as its software implementation, to compare two samples by a nonparametric likelihood-ratio test. The basis of the comparison is a mean-type hypothesis. The software is written in the R-language [4]. The two samples are assumed to be independent. Their distributions, which are assumed to be unknown, may be discrete or continuous. The samples may be uncensored, right-censored, left-censored, or doubly-censored. Two software programs are offered. The first program covers the case of a single mean-type hypothesis. The second program covers the case of multiple mean-type hypotheses. For the first …


Nonparametric Estimation Of Derivatives With Applications, Benjamin Hall Jan 2010

Nonparametric Estimation Of Derivatives With Applications, Benjamin Hall

University of Kentucky Doctoral Dissertations

We review several nonparametric regression techniques and discuss their various strengths and weaknesses with an emphasis on derivative estimation and confidence band creation. We develop a generalized C(p) criterion for tuning parameter selection when interest lies in estimating one or more derivatives and the estimator is both linear in the observed responses and self-consistent. We propose a method for constructing simultaneous confidence bands for the mean response and one or more derivatives, where simultaneous now refers both to values of the covariate and to all derivatives under consideration. In addition we generalize the simultaneous confidence bands to account for heteroscedastic …