Memet Ali Cengiz
Department of Statistics, University of Ondokuz Mayis, Samsun, Turkey
Yuksel Bek
Department of Biostatistics, University of Ondokuz Mayis, Sam sun, Turkey
Rezan Yilmaz
Department of Statistics, University of Ondokuz Mayis, Samsun, Turkey
ABSTRACT
Response variables having two possible categories are called binary variables. We often describe two possible categories as the terms of disease and healthy. Binary response data are modelled using the binomial distribution while binary data may be assumed to have the Bernoulli distribution which is a special case of the binomial distribution. This paper investigates logistic regression model to improve the accuracy of predictions and decisions, in the specific context of assessing erythrocyte sedimentation rate. The analysis is enhanced further by adopting a Bayesian approach.
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How to cite this article
Memet Ali Cengiz, Yuksel Bek and Rezan Yilmaz, 2001. Bayesian Inference of Binary Logistic Regression Model for Assessing Erythrocyte Sedimentation Rate. Pakistan Journal of Biological Sciences, 4: 1180-1183.
DOI: 10.3923/pjbs.2001.1180.1183
URL: https://scialert.net/abstract/?doi=pjbs.2001.1180.1183
DOI: 10.3923/pjbs.2001.1180.1183
URL: https://scialert.net/abstract/?doi=pjbs.2001.1180.1183
REFERENCES
- Sox, H.C.J. and M.H. Liang, 1986. The erythrocyte sedimentation rate: Guidelines for rational use. Ann. Int. Med., 104: 515-523.
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