Journal of Mathematics and Statistics

Optimization Techniques for Variable Selection in Binary Logistic Regression Model Applied to Desire for Children Data

S. K. Sarkar and Habshah Midi

DOI : 10.3844/jmssp.2009.387.394

Journal of Mathematics and Statistics

Volume 5, Issue 4

Pages 387-394

Abstract

Problem statement: The population problem is the biggest problem in the world. In the global and regional context, Bangladesh population has drawn considerable attention of the social scientists, policy makers and international organizations. Bangladesh is now world’s 10th populous country having about 140 million people. The recent experience of Bangladesh shows that fertility can sustain impressive declines even when women’s lives remain severely constrained. Recent statistics also suggest that, despite a continuing increase in contraceptive prevalence rate (56%), the expected fertility decline in Bangladesh has stalled. Approach: The purpose of this study was to explore the possibility of further fertility decline in Bangladesh with special attention to identify some social and demographic factors as predictors which are responsible to desire for more children using stepwise and best subsets logistic regression approaches. The study had compared two approaches to determine an optimum model for prediction of the outcome. Results: It had been found, excess desire for children is solely responsible for the stalled fertility. Conclusion: To overcome the situation, the policy makers of Bangladesh should pay their attention to eliminate the regional variations of desire for more children and introduce awareness programs among rural women about the positive impact of smaller family.

Copyright

© 2009 S. K. Sarkar and Habshah Midi. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.