Analysis of Antenatal Care Visit Data in Bangladesh Using Zero Modified Count Regression Model

N. Ahmed, T. S. Mallick
{"title":"Analysis of Antenatal Care Visit Data in Bangladesh Using Zero Modified Count Regression Model","authors":"N. Ahmed, T. S. Mallick","doi":"10.3329/dujs.v67i2.54583","DOIUrl":null,"url":null,"abstract":"In medical science, pharmaceutical studies, public health and socio-economic researches we often encounter the situation of excess of zeros in count data. This preponderance of zeros leads to overdispersion. In such cases traditional count data regression models like Poisson and negative binomial (NB) regression may not be pertinent for inference. The two most commonly used types of model that have been developed to adjust for excessivezeros in count data are Hurdle and zero-inflated models. In this study we have analyzed the antenatal care (ANC) visit data of pregnant women in Bangladesh using traditional and zero-modified count models. Based on the model selection criteria, we found that negative binomial hurdle model fits the data best. Through this analysis,we have perceived that the variables age of mother, division, birth order (order a child is born), place of residence, economic condition, media exposure of the mother, mainaccess road to village and education gap between husband and wife have significant impact on the mean number of ANC visits taken. Dhaka Univ. J. Sci. 67(2): 117-122, 2019 (July)","PeriodicalId":11280,"journal":{"name":"Dhaka University Journal of Science","volume":"12 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dhaka University Journal of Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3329/dujs.v67i2.54583","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In medical science, pharmaceutical studies, public health and socio-economic researches we often encounter the situation of excess of zeros in count data. This preponderance of zeros leads to overdispersion. In such cases traditional count data regression models like Poisson and negative binomial (NB) regression may not be pertinent for inference. The two most commonly used types of model that have been developed to adjust for excessivezeros in count data are Hurdle and zero-inflated models. In this study we have analyzed the antenatal care (ANC) visit data of pregnant women in Bangladesh using traditional and zero-modified count models. Based on the model selection criteria, we found that negative binomial hurdle model fits the data best. Through this analysis,we have perceived that the variables age of mother, division, birth order (order a child is born), place of residence, economic condition, media exposure of the mother, mainaccess road to village and education gap between husband and wife have significant impact on the mean number of ANC visits taken. Dhaka Univ. J. Sci. 67(2): 117-122, 2019 (July)
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
使用零修正计数回归模型分析孟加拉国产前保健访问数据
在医学、药物研究、公共卫生和社会经济研究中,我们经常遇到计数数据中超过零的情况。这种零的优势导致过色散。在这种情况下,传统的计数数据回归模型,如泊松和负二项回归(NB)可能不适合推理。为调整计数数据中过多的零而开发的两种最常用的模型类型是障碍模型和零膨胀模型。在本研究中,我们使用传统和零修改计数模型分析了孟加拉国孕妇的产前护理(ANC)访问数据。根据模型选择标准,我们发现负二项障碍模型最适合数据。通过这一分析,我们发现,母亲的年龄、分工、出生顺序(孩子出生的顺序)、居住地、经济条件、母亲的媒体曝光率、通往村庄的主要通道以及夫妻之间的教育差距等变量对ANC的平均访问次数有显著影响。达卡大学学报(自然科学版),67(2):117- 122,2019 (7)
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
自引率
0.00%
发文量
0
期刊最新文献
Covid-19 Pandemic and Pre-pandemic Economic Shocks to Brazil, India, and Mexico: A Forecast Comparison Evaluating the Impact and Recovery New Traveling Wave Solutions to the Simplified Modified Camassa–Holm Equation and the Landau-Ginsburg-Higgs Equation Phytochemical Investigation and Biological Studies of Coffea benghalensis B. Heyne Ex Schult Synthesis and Characterization of Vanadium Doped Hexagonal Rubidium Tungsten Bronze Preparation and Characterization of Porous Carbon Material from Banana Pseudo-Stem
×
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