Please use this identifier to cite or link to this item:
Title: Robust estimation for longitudinal data with informative observation times
Authors: Liu, Kin Yat
Advisors: Zhao, Xingqiu (AMA)
Keywords: Longitudinal method.
Regression analysis.
Medicine -- Research -- Statistical methods.
Issue Date: 2014
Publisher: The Hong Kong Polytechnic University
Abstract: In this thesis, we focus on regression analysis of longitudinal data that often occur in medical follow-up studies and observational investigations. The analysis of these data involves two processes. One is the underlying recurrent event process of interest and the other is the observation process that controls observation times. Most of the existing methods, however, rely on some restrictive models or assumptions such as the Poisson assumption. For this, we propose a more general and robust estimation approach for regression analysis of longitudinal data with related observation times. The asymptotic properties of the proposed estimators are established and numerical studies indicate that the proposed method works well for practical situations.
Description: PolyU Library Call No.: [THS] LG51 .H577M AMA 2014 Liu
53 leaves ;30 cm
Rights: All rights reserved.
Appears in Collections:Thesis

Files in This Item:
File Description SizeFormat 
b28068270_link.htmFor PolyU Users203 BHTMLView/Open
b28068270_ir.pdfFor All Users (Non-printable)818.29 kBAdobe PDFView/Open
Show full item record

Page view(s)

Last Week
Last month
Citations as of Mar 19, 2018


Citations as of Mar 19, 2018

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.