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Semiparametric analysis of panel count data with correlated observation and follow-up times.

Authors
He-X; Tong-X; Sun-J
Source
Lifetime Data Anal 2009 Jun; 15(2):177-196
NIOSHTIC No.
20035645
Abstract
This paper discusses regression analysis of panel count data that often arise in longitudinal studies concerning occurrence rates of certain recurrent events. Panel count data mean that each study subject is observed only at discrete time points rather than under continuous observation. Furthermore, both observation and follow-up times can vary from subject to subject and may be correlated with the recurrent events. For inference, we propose some shared frailty models and estimating equations are developed for estimation of regression parameters. The proposed estimates are consistent and have asymptotically a normal distribution. The finite sample properties of the proposed estimates are investigated through simulation and an illustrative example from a cancer study is provided.
Keywords
Analytical-methods; Analytical-models; Analytical-processes; Cancer-rates; Exposure-levels; Exposure-methods Mathematical-models; Mortality-surveys; Statistical-analysis; Therapeutic-agents; Treatment; Workplace-studies; Author Keywords: Estimating equation; Informative follow-up time; Informative observation times; Mean function model; Regression analysis
Contact
Xin He, Division of Biostatistics, College of Public Health, The Ohio State University, B-116 Starling-Loving Hall, 320 West 10th Avenue, Columbus, OH 43210
CODEN
LDANFI
Publication Date
20090601
Document Type
Journal Article
Email Address
xhe@cph.osu.edu
Funding Type
Grant
Fiscal Year
2009
NTIS Accession No.
NTIS Price
Identifying No.
Grant-Number-R01-OH-008649
Issue of Publication
2
ISSN
1380-7870
Source Name
Lifetime Data Analysis
State
OH; MO
Performing Organization
Ohio State University
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