Abstract
The number of ever born children is one of the main components of population dynamics that determine the size, structure, as well as the composition of a countries’ population. Children ever born refer to the number of children born alive to the person up to a specified reference date and served as a response variable here. A secondary dataset is used in this paper that is obtained from a countrywide representative survey entitled Bangladesh Demographic and Health Survey (BDHS) 2014. This study aims to identify the socioeconomic and demographic factors influencing children ever born to the women of 15-49 years old in Bangladesh. The first attempt of this paper is to identify the best-fitted model among generalized Poisson, Negative Binomial, truncated, COM and finite mixture regression model form. The results suggest that among the model considered in this study Finite Mixture Negative Binomial Regression with three components gives the best-fitted model to estimate the number of ever born children in Bangladesh. It reveals that respondents age, residential status, family size and intention of using contraception have shown positive impact and respondents education, drinking water, toilet facility, religious status, household head age, wealth index, age at first birth, and husband education shows a negative impact on ever born children.
Original language | English |
---|---|
Title of host publication | Statistics for data science and policy analysis |
Editors | Azizur Rahman |
Place of Publication | Singapore |
Publisher | Springer |
Chapter | 17 |
Pages | 221-236 |
Number of pages | 16 |
ISBN (Electronic) | 9789811517358 |
ISBN (Print) | 9789811517341 |
DOIs | |
Publication status | Published - Apr 2020 |
Event | The 2nd Applied Statistics and Policy Analysis Conference: ASPAC2019 - Charles Sturt University, Wagga Wagga, Australia Duration: 05 Sept 2019 → 06 Sept 2019 http://csusap.csu.edu.au/~azrahman/ASPAC2019/ http://csusap.csu.edu.au/~azrahman/ASPAC2019/Program%20draft.pdf?attredirects=0&d=1 (program) http://csusap.csu.edu.au/~azrahman/ASPAC2019/ASPAC2019_Refereed_Book%20of%20Abstracts.pdf?attredirects=0&d=1 (book of abstracts) https://ebookcentral.proquest.com/lib/CSUAU/detail.action?docID=6152166 (proceedings) |
Conference
Conference | The 2nd Applied Statistics and Policy Analysis Conference |
---|---|
Abbreviated title | Effective policy through the use of big data, accurate estimates and modern computing tools and statistical modelling |
Country/Territory | Australia |
City | Wagga Wagga |
Period | 05/09/19 → 06/09/19 |
Other | Proceedings due for publication May 2020 https://www.springer.com/gp/book/9789811517341 |
Internet address |
|
Fingerprint
Dive into the research topics of 'Finite mixture modelling approach to identify factors affecting children ever born for 15-49 year old women in Asian country'. Together they form a unique fingerprint.Impacts
-
Statistics is an essence for data science and policy analysis
Rahman, A. (Creator)
Impact: Social Impact, Public policy Impact, Quality of life Impact
File