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Pakistan Journal of Biological Sciences

Year: 2001 | Volume: 4 | Issue: 9 | Page No.: 1180-1183
DOI: 10.3923/pjbs.2001.1180.1183
Bayesian Inference of Binary Logistic Regression Model for Assessing Erythrocyte Sedimentation Rate
Memet Ali Cengiz, Yuksel Bek and Rezan Yilmaz

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.

Keywords: bayesian inference, logistic model, ESO and binomial distribution

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