Biomedical Engineering Reference
In-Depth Information
Chapter 4
Regression Analysis for Current
Status Data
Bin Zhang
Department of Biostatistics and Epidemiology, Cincinnati Children's Hospital
Medical Center, Cincinnati, Ohio, USA
4.1
Introduction ::::::::::::::::::::::::::::::::::::::::::::::::::::::
91
4.2
Regression Analysis with Proportional Hazards Model :::::::::
93
4.3
Regression Analysis with Proportional Odds Model :::::::::::::
97
4.4
Regression Analysis with Linear Transformation Model :::::::: 100
4.5
Bivariate Current Status Data with Proportional Odds Model : 101
4.6
Illustrative Examples ::::::::::::::::::::::::::::::::::::::::::::: 104
4.7
Discussion and Remarks ::::::::::::::::::::::::::::::::::::::::: 107
Bibliography :::::::::::::::::::::::::::::::::::::::::::::::::::::: 109
4.1
Introduction
Current status data, which is also known as type I interval-censored data,
arise naturally in many applications including animal tumorigenicity experi-
ments, HIV and AIDS studies, demographic studies, econometrics, and epi-
demiological studies. In these studies, the variable of interest is the time to
the occurrence of a certain event, such as the tumor onset. By current status
data, we mean that each study subject is observed only at one time point and
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