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Activity Number:
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405
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Type:
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Contributed
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Date/Time:
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Wednesday, August 6, 2008 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #301982 |
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Title:
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Modeling Generalized Linear Mixed Models in S-PLUS, R, and SAS
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Author(s):
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Stella Karuri*+ and Tim Hesterberg and Chris Fraley
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Companies:
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Insightful Corporation and Google, Inc. and Insightful Corporation
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Address:
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1700 Westlake Avenue, Seattle, WA, 98109,
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Keywords:
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generalized mixed models ; laplace estimation ; penalized quasi likelihood ; maximum likelihood
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Abstract:
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Generalized Linear Mixed Models (GLMMS) are popular in modeling clustered data. We survey existing routines for fitting GLMMS implemented in R, S-PLUS and SAS, and find that all routines fail in some situations. We describe a new S-PLUS routine, based on Spherical Radial Quadrature that offers more reliable estimation.
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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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