Date on Master's Thesis/Doctoral Dissertation
5-2016
Document Type
Doctoral Dissertation
Degree Name
Ph. D.
Department
Bioinformatics and Biostatistics
Degree Program
Biostatistics, PhD
Committee Chair
Datta, Somnath
Committee Member
Datta, Susmita
Committee Member
Kulasekera, K.B
Committee Member
Mitra, Riten
Committee Member
Gill, Ryan
Author's Keywords
rank-test; pseudo-value; jackknife; survival
Abstract
This dissertation is composed of research projects that involve methods which can be broadly classified as either nonparametric or semiparametric. Chapter 1 provides an introduction of the problems addressed in these projects, a brief review of the related works that have done so far, and an outline of the methods developed in this dissertation. Chapter 2 describes in details the first project which aims at developing a rank-sum test for clustered data where an outcome from group in a cluster is associated with the number of observations belonging to that group in that cluster. Chapter 3 proposes the use of pseudo-value regression (Andersen, Klein, and Rosthøj, 2003) in combination with penalized and latent factor regression techniques for prediction of future state occupation in a multistate model based on high dimensional baseline covariates. Chapter 4 describes the development of an R package involving various rank based tests for clustered data which are useful in situations where the number of outcomes in a cluster or in a particular group within a cluster is informative. Chapter 5 explains the fouth project which aims at developing a covariate-adjusted rank-sum test for clustered data through alingned rank transformation.
Recommended Citation
Dutta, Sandipan, "Some contributions to nonparametric and semiparametric inference for clustered and multistate data." (2016). Electronic Theses and Dissertations. Paper 2454.
https://doi.org/10.18297/etd/2454
