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Bayesian non-parametric methods for benefit-risk assessment and massive multiple-domain data
(University of Missouri--Columbia, 2019)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The development of systematic and structured approaches to assess benefit-risk of medical products is a major challenge for regulatory decision makers. ...
Dynamic analysis of complex panel count data
(University of Missouri--Columbia, 2021)
Panel count data occur in many fields including clinical, demographical and industrial studies and an extensive literature has been established for their regression analysis. However, most of the existing methods apply ...
Variable selection for interval-censored failure time data
(University of Missouri--Columbia, 2019)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Variable selection is a commonly asked question and various traditional variable selection methods have been developed, including forward, backward and ...
Statistical methods to deflect allele specific expression, alterations of allele specific expression and differential expression
(University of Missouri--Columbia, 2021)
are significantly different across treatment groups (DE genes). In Chapter 2, we propose a method to test ASE of a gene as a whole and variation in ASE within a gene across exons separately and simultaneously. A generalized linear mixed model is employed...
Semiparametric analysis of complex longitudinal data
(University of Missouri--Columbia, 2020)
Event history data consist of the longitudinal records of event occurrence times. Recurrent event data and panel count data are two common types of event history data that occur in many areas, such as medical studies and ...