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Statistical considerations in the analysis of multivariate Phase II testing.
(2009-04-01)
In medical diagnosis and treatment, many diseases are characterized by multiple measurable differences in clinical (e.g., physical or radiological differences) and laboratory parameters (biomarkers from "healthy levels". ...
Multivariate analyses of near-infrared and UV spectral data.
(2009-07-01)
Various chemometric analyses were applied to spectroscopic data with goals to develop alternative methods that could be employed in government or industrial settings. With the concerns of these organizations in mind, the ...
Multivariate analysis of luminescence spectra as a means of determining postmortem interval.
(, 2011-09-14)
Post-mortem interval (PMI) is the time elapsed since a person died. Currently there is no accurate method for determining PMI of skeletal remains. Existing methods are best suited for deciding whether a bone is of forensic ...
A restriction method for the analysis of discrete longitudinal missing data.
(2007-02-07)
Clinical trial endpoints are traditionally either physical or laboratory responses. However, such endpoints fail to reflect how patients feel or function in their daily activities. Missing data is inevitable in most every ...
Selected topics in statistical discriminant analysis.
(2007-02-07)
This dissertation consists of three selected topics in statistical discriminant analysis: dimension reduction, regularization methods, and imputation methods. In Chapter 2 we first derive a new linear dimension-reduction ...
Application of chemometric analysis to UV-visible and diffuse near-infrared reflectance spectra.
(2007-08-21)
Multivariate analysis of spectroscopic data has become more common place in analytical investigations due to several factors, including diode-array spectrometers, computer-assisted data acquisition systems, and chemometric ...
Logistic regression with misclassified response and covariate measurement error: a Bayesian approach.
(2007-12-04)
In a variety of regression applications, measurement problems are unavoidable because infallible measurement tools may be expensive or unavailable. When modeling the relationship between a response variable and covariates, ...