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Bayesian Inference of Binary Logistic Regression Model for Assessing Erythrocyte Sedimentation Rate

Author(s): Memet Ali Cengiz | Yuksel Bek | Rezan Yilmaz

Journal: Pakistan Journal of Biological Sciences
ISSN 1028-8880

Volume: 4;
Issue: 9;
Start page: 1180;
Date: 2001;
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Keywords: ESO | logistic model | bayesian inference | binomial distribution

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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