Regression Estimation of Bongaart Indices from the Childbearing Indices: A Study of India/States/Districts

IF 0.3 Q4 MULTIDISCIPLINARY SCIENCES Momona Ethiopian Journal of Science Pub Date : 2019-05-30 DOI:10.4314/MEJS.V11I1.7
K. M. Ponnapalli, Akash Kumar
{"title":"Regression Estimation of Bongaart Indices from the Childbearing Indices: A Study of India/States/Districts","authors":"K. M. Ponnapalli, Akash Kumar","doi":"10.4314/MEJS.V11I1.7","DOIUrl":null,"url":null,"abstract":"In a series of research articles El-khorazaty, Horne and Suchindran have showed how one can derive for any given population indirectly various childbearing and Bongaart fertility-inhibiting indices using only given information on the ASFRs, and the mathematical and regression models suggested by them. Very recently Bongaart revised his old model and suggested a set of new revised formulae to estimate various fertility-inhibiting indices. Following El-Khorazaty and Horne it is aimed to show in the present paper how one can derive various Bongaart revised fertility-inhibiting indices from the given information on various childbearing indices which were further seen derived from the only given information on TFR and a set of regression models that were earlier suggested by the first author and it is shown that the present study succeed in giving meaningful estimates for India its States, UTs, and Districts. Various regression models referring to estimation of childbearing indices used in this study were developed earlier by Ponnapalli using the state level time series of ASFRs overtime of the SRS of India and Horne et al., mathematical model. The regression models used in indirect estimation of the fertility-inhibiting indices from the TFR and also from the childbearing indices were developed by Ponnapalli using the Bongart indices of the DHS surveys earlier given by Bongaart in his revised recent study. Keywords:  Fertility; Childbearing indices; Indirect Estimation; Bongaart Indices; ASFRs; TFR; TF; India","PeriodicalId":18948,"journal":{"name":"Momona Ethiopian Journal of Science","volume":" ","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2019-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4314/MEJS.V11I1.7","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Momona Ethiopian Journal of Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4314/MEJS.V11I1.7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

In a series of research articles El-khorazaty, Horne and Suchindran have showed how one can derive for any given population indirectly various childbearing and Bongaart fertility-inhibiting indices using only given information on the ASFRs, and the mathematical and regression models suggested by them. Very recently Bongaart revised his old model and suggested a set of new revised formulae to estimate various fertility-inhibiting indices. Following El-Khorazaty and Horne it is aimed to show in the present paper how one can derive various Bongaart revised fertility-inhibiting indices from the given information on various childbearing indices which were further seen derived from the only given information on TFR and a set of regression models that were earlier suggested by the first author and it is shown that the present study succeed in giving meaningful estimates for India its States, UTs, and Districts. Various regression models referring to estimation of childbearing indices used in this study were developed earlier by Ponnapalli using the state level time series of ASFRs overtime of the SRS of India and Horne et al., mathematical model. The regression models used in indirect estimation of the fertility-inhibiting indices from the TFR and also from the childbearing indices were developed by Ponnapalli using the Bongart indices of the DHS surveys earlier given by Bongaart in his revised recent study. Keywords:  Fertility; Childbearing indices; Indirect Estimation; Bongaart Indices; ASFRs; TFR; TF; India
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
从生育指数回归估计Bongaart指数:对印度/邦/地区的研究
在一系列研究文章中,El-khorazaty、Horne和Suchindran展示了如何仅使用ASFRs的给定信息,以及它们提出的数学和回归模型,就可以间接地为任何给定的人口推导出各种生育和Bongaart生育抑制指数。最近,邦加特修改了他的旧模型,并提出了一套新的修正公式来估计各种生育抑制指数。继El-Khorazaty和Horne之后,本论文旨在展示如何从各种生育指数的给定信息中推导出各种Bongaart修订的生育抑制指数,这些指数进一步从唯一给定的TFR信息和第一作者先前提出的一组回归模型中推导出来,并表明本研究成功地为印度的州,UTs和地区提供了有意义的估计。本研究中使用的生育指标估计的各种回归模型是Ponnapalli早先利用印度SRS的ASFRs超时的邦级时间序列和Horne等数学模型开发的。用于间接估计TFR和生育指数的生育抑制指数的回归模型是由Ponnapalli根据Bongaart在他最近修订的研究中早先给出的DHS调查的Bongart指数开发的。关键词:生育;生育指标;间接估计;Bongaart指数;ASFRs;总和生育率;特遣部队;印度
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Momona Ethiopian Journal of Science
Momona Ethiopian Journal of Science MULTIDISCIPLINARY SCIENCES-
自引率
0.00%
发文量
13
审稿时长
12 weeks
期刊最新文献
First occurrence of rudderfish Centrolophus niger (Gmelin, 1789) in the Edremit Bay (Northern Aegean Sea, Türkiye) with the maximum length record for Turkish Seas An Engineering Geological Appraisal of the Leakage Problem in Dora-1 Earthen Dam, Tigray: Implications for its Stability Nano-Zirconia Synthesis Methods and their Pioneering Applications in Dentistry Contribution of Participatory Forest Management Program in Non-Timber Forest Products to balance Livelihood Improvement and Conservation: a case of Sera Forest, Amigna District, Southern Ethiopia Effect of Polymerization Variables on the Electrical Conductivity of Polyaniline Functionalized Cotton Textiles
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1