Cover Image

Survival modeling of first birth interval after marriage

This is a data exploratory analysis of retrospective cross-sectional study of pattern of first birth interval after marriage in Nigeria. The data for the study are extracted from the published reports of the National Demographic and Health Survey 2009 edition. Fertility as a major component of popul...

Full description

Saved in:
Bibliographic Details
Main Authors: Simeon, Amusan Ajitoni, Mohd. Khalid, Zarina
Format: Article
Published: Zhengzhou University 2014
Subjects:
Q Science
Online Access:http://eprints.utm.my/id/eprint/62743/
http://www.lifesciencesite.com/lsj/life1107/035_23903life110714_299_307.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.62743
record_format eprints
spelling my.utm.627432017-06-06T06:10:10Z http://eprints.utm.my/id/eprint/62743/ Survival modeling of first birth interval after marriage Simeon, Amusan Ajitoni Mohd. Khalid, Zarina Q Science This is a data exploratory analysis of retrospective cross-sectional study of pattern of first birth interval after marriage in Nigeria. The data for the study are extracted from the published reports of the National Demographic and Health Survey 2009 edition. Fertility as a major component of population change is influenced by first birth interval after marriage, since the interval is positively correlated with the cumulative number of children a woman would have at the end of her reproductive life. Studies have described this interval using non-parametric methods which lack features to project the estimates further. This paper is designed to fill the gap by attempting to fit a parametric model to data on the first birth interval among women of reproductive age in Nigeria. Four parametric models whose various curves and estimates are compared with non-parametric values are considered, namely Inverse Gaussian, Log-logistic, Weibull and Burr Type XII. The best model appears to be Inverse Gaussian based on the Akaike Information Criterion of lowest value of 116617.6. Quantile-quantile plots also identify Inverse Gaussian as model whose data points clustered much around straight line. All other curves give credence to the Inverse Gaussian model as the one that describes the data better than the rest. However, the study does not rule out adaptability of Log-logistic distribution to model waiting time to first birth after marriage since it also behaves similarly to Inverse Gaussian distribution. Zhengzhou University 2014 Article PeerReviewed Simeon, Amusan Ajitoni and Mohd. Khalid, Zarina (2014) Survival modeling of first birth interval after marriage. Life Science Journal, 11 (7). pp. 299-307. ISSN 1097-8135 http://www.lifesciencesite.com/lsj/life1107/035_23903life110714_299_307.pdf
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic Q Science
spellingShingle Q Science
Simeon, Amusan Ajitoni
Mohd. Khalid, Zarina
Survival modeling of first birth interval after marriage
description This is a data exploratory analysis of retrospective cross-sectional study of pattern of first birth interval after marriage in Nigeria. The data for the study are extracted from the published reports of the National Demographic and Health Survey 2009 edition. Fertility as a major component of population change is influenced by first birth interval after marriage, since the interval is positively correlated with the cumulative number of children a woman would have at the end of her reproductive life. Studies have described this interval using non-parametric methods which lack features to project the estimates further. This paper is designed to fill the gap by attempting to fit a parametric model to data on the first birth interval among women of reproductive age in Nigeria. Four parametric models whose various curves and estimates are compared with non-parametric values are considered, namely Inverse Gaussian, Log-logistic, Weibull and Burr Type XII. The best model appears to be Inverse Gaussian based on the Akaike Information Criterion of lowest value of 116617.6. Quantile-quantile plots also identify Inverse Gaussian as model whose data points clustered much around straight line. All other curves give credence to the Inverse Gaussian model as the one that describes the data better than the rest. However, the study does not rule out adaptability of Log-logistic distribution to model waiting time to first birth after marriage since it also behaves similarly to Inverse Gaussian distribution.
format Article
author Simeon, Amusan Ajitoni
Mohd. Khalid, Zarina
author_facet Simeon, Amusan Ajitoni
Mohd. Khalid, Zarina
author_sort Simeon, Amusan Ajitoni
title Survival modeling of first birth interval after marriage
title_short Survival modeling of first birth interval after marriage
title_full Survival modeling of first birth interval after marriage
title_fullStr Survival modeling of first birth interval after marriage
title_full_unstemmed Survival modeling of first birth interval after marriage
title_sort survival modeling of first birth interval after marriage
publisher Zhengzhou University
publishDate 2014
url http://eprints.utm.my/id/eprint/62743/
http://www.lifesciencesite.com/lsj/life1107/035_23903life110714_299_307.pdf
_version_ 1643655509548466176
score 13.211869

Similar Items