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Activity Number:
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276
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Type:
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Contributed
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Date/Time:
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Tuesday, August 4, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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| Abstract - #304555 |
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Title:
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Semiparametric Analysis of Panel Count Data with Correlated Observation and Follow-Up Times
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Author(s):
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Xin He*+ and Xingwei Tong and Jianguo Sun
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Companies:
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The Ohio State University and Beijing Normal University and University of Missouri
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Address:
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B-116 Starling-Loving Hall, Columbus, OH, 43210,
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Keywords:
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Estimating equation ; Informative follow-up time ; Informative observation times ; Mean function model ; Regression analysis
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Abstract:
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This talk 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.
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