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Journal of Applied Sciences
  Year: 2005 | Volume: 5 | Issue: 7 | Page No.: 1228-1231
DOI: 10.3923/jas.2005.1228.1231
 
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Generalized Estimating Equations for Conditional and Unconditional Residuals in Diabetes Mellitus Data

Md. Abdus Salam Akanda, Kawsar Jahan, Maksuda Khanam and M. Ataharul Islam

Abstract:
This study focused for estimating the parameters of marginal model for repeated binary responses through the Generalized Estimating Equations (GEE) methodology. The GEE were applied to observe how certain covariates relate to change of the disease status overtime. In addition, we focused on the methodology of GEE using conditional and unconditional residuals along with common correlation structures seen in longitudinal studies. Here, the GEE has been applied to the data of four repeated binary observations of the registered patients at BIRDEM. We demonstrate that the estimator of the correlation based on conditional residuals is nearly efficient when compared with maximum likelihood. This estimator also yields more efficient estimates of the correlation than the usual GEE estimator that is based on unconditional residuals. Finally the results of applying the data set are presented.
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How to cite this article:

Md. Abdus Salam Akanda, Kawsar Jahan, Maksuda Khanam and M. Ataharul Islam, 2005. Generalized Estimating Equations for Conditional and Unconditional Residuals in Diabetes Mellitus Data. Journal of Applied Sciences, 5: 1228-1231.

DOI: 10.3923/jas.2005.1228.1231

URL: https://scialert.net/abstract/?doi=jas.2005.1228.1231

COMMENTS
07 July, 2011
Prof. Hoang Xuan Phu :
This is an interesting piece of scientific research work on GEE.
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