Advanced techniques for modelling maternal and child health in Africa [electronic resource]
- 其他作者：
- 其他題名：
- Springer series on demographic methods and population analysis ;
- 出版： Dordrecht : Springer Netherlands :Imprint: Springer
- 叢書名： The Springer Series On Demographic Methods and Population Analysis,
- 主題： Children--Health and hygiene--Africa--Statistical methods. , Maternal health services--Africa--Statistical methods. , Social Sciences , Demography. , Maternal and Child Health. , Statistics for Life Sciences, Medicine, Health Sciences. , Methodology of the Social Sciences.
- ISBN： 9789400767782 (electronic bk.) 、 9789400767775 (paper)
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FIND@SFXID:
CGU
- 資料類型: 電子書
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讀者標籤：
- 系統號： 005114628 | 機讀編目格式
館藏資訊
This book presents both theoretical contributions and empirical applications of advanced statistical techniques including geo-additive models that link individual measures with area variables to account for spatial correlation; multilevel models that address the issue of clustering within family and household; multi-process models that account for interdependencies over life-course events and non-random utilization of health services; and flexible parametric alternatives to existing intensity models. These analytical techniques are illustrated mainly through modeling maternal and child health in the African context, using data from demographic and health surveys. In the past, the estimation of levels, trends and differentials in demographic and health outcomes in developing countries was heavily reliant on indirect methods that were devised to suit limited or deficient data. In recent decades, world-wide surveys like the World Fertility Survey and its successor, the Demographic and Health Survey have played an important role in filling the gap in survey data from developing countries. Such modern demographic and health surveys enable investigators to make in-depth analyses that guide policy intervention strategies, and such analyses require the modern and advanced statistical techniques covered in this book. The text is ideally suited for academics, professionals, and decision makers in the social and health sciences, as well as others with an interest in statistical modelling, demographic and health surveys. Scientists and students in applied statistics, epidemiology, medicine, social and behavioural sciences will find it of value.