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Activity Number:
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517
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Type:
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Invited
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Date/Time:
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Thursday, August 2, 2007 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #307677 |
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Title:
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A Class of Linear Transformation Models Under Interval Censoring
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Author(s):
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Zhigang Zhang*+
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Companies:
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Oklahoma State University
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Address:
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301C MSCS, Dept. of Statistics, Stillwater, OK, 74078,
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Keywords:
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Linear transformation models ; interval censoring ; regression analysis
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Abstract:
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Regression analysis of interval-censored failure time data has recently attracted a great deal of attention and for the problem, several methods have been proposed. However, most of these methods employ specific models such as the proportional hazards model. The linear transformation models, a class of generalized proportional hazards models, provide great flexibility in fitting survival data. Although the application of these models on right-censored data has been discussed, the only existing inference procedure for the linear transformation models when interval-censored data are observed is limited to multi-sample situations and lacks rigorous technical justification. In this study we present approaches that allow the covariate to be arbitrary and provide a theoretical framework.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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