Manuscript Number : IJSRST151537
An Investigation of Malaria Predictors Using Logistic Regression Model
Authors(3) :-Abubakar Boyi Dalatu, Mukhtar Garba, Nwoji Jude Oguejiofor
Although malaria is a disease which is considered the most deadly killer especially to children less than 5 years mainly of African countries, there exists no statistical model for the analysis of its predictors for the case of Kebbi State. In this work a logistic regression model using maximum likelihood estimation is proposed. The application of the model using Kebbi State malaria data established that there is significant relationship between malaria status and such predictors as fever, temperature greater than or equal to 37.5 degree, headache, convulsions, cold, cough or sweating, etc. While age, sex, backache and vomiting are not good predictors of malaria. Doctors, medical practitioners and researchers will find this model useful in predicting malaria prevalence.
Abubakar Boyi Dalatu
Logit Function, Logistic regression, Maximum Likelihood Estimation
Publication Details
Published in :
Volume 1 | Issue 5 | November-December 2015 Article Preview
Department of Statistics, Waziri Umaru Federal Polytechnic Birnin Kebbi, Nigeria
Mukhtar Garba
Department of Statistics, Waziri Umaru Federal Polytechnic Birnin Kebbi, Nigeria
Nwoji Jude Oguejiofor
Department of Computer Science, Waziri Umaru Federal Polytechnic Birnin Kebbi, Nigeria
Date of Publication :
2015-12-25
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) :
153-157
Manuscript Number :
IJSRST151537
Publisher : Technoscience Academy
Journal URL :
http://ijsrst.com/IJSRST151537