Title of article :
Analysis of clustered data: A combined estimating equations approach
Author/Authors :
A.Stoner، Julie نويسنده , , G.Leroux، Brian نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2002
Pages :
-566
From page :
567
To page :
0
Abstract :
Examples of clustered data include data from longitudinal studies and data sampled within groups.This paper proposes a regression analysis method for clustered data that optimally weights and combines contrasts of the data through a combination of estimating equations. Examples of combining between-cluster, within-cluster and longitudinal data contrasts are presented. The method results in increased estimation efficiency relative to generalised estimating equations with standard working correlation structures. The proposed method also simplifies modelling decisions regarding the true correlation structure of the data and avoids correlation parameter estimation.
Keywords :
Generalised linear model , Batch importance sampling , importance sampling , Markov chain Monte Carlo , Parallel processing , Metropolis–Hastings , Mixture model , Particle filter
Journal title :
Biometrika
Serial Year :
2002
Journal title :
Biometrika
Record number :
71788
Link To Document :
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