2019
DOI: 10.1007/s42650-019-00014-7
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Estimating the Underlying Infant Mortality Rates for Small Populations, Even Those Reporting Zero Infant Deaths: a Case Study of 66 Local Health Areas in British Columbia

Abstract: Your article is protected by copyright and all rights are held exclusively by Springer Nature Switzerland AG. This e-offprint is for personal use only and shall not be selfarchived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledg… Show more

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Cited by 2 publications
(2 citation statements)
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“…3 This paper illustrates one such use with a sub-set of the mortality component, the infant mortality rate. Although we focus on an African application, the method can be applied to many other situations where small, inherently binomial, numbers are present and affected by stochastic uncertainty, whether they are from a scientific sample, as is the case in this paper, or a "complete count" as found in a reliable vital registration system [17].…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…3 This paper illustrates one such use with a sub-set of the mortality component, the infant mortality rate. Although we focus on an African application, the method can be applied to many other situations where small, inherently binomial, numbers are present and affected by stochastic uncertainty, whether they are from a scientific sample, as is the case in this paper, or a "complete count" as found in a reliable vital registration system [17].…”
Section: Discussionmentioning
confidence: 99%
“…Before turning to a description of our method and the data we employed, it is appropriate to provide an overview of what our approach aims to do. Stochastic uncertainty reflects the fact that even where the underlying IMR is constant in a small population over time, empirical observations of it can fluctuate from year to year even if it is measured from a complete count of the events of interest [17]. As such, the approach described regarding to revising sample-based IMR estimates is aimed at taking into account stochastic uncertainty while preserving the information concerning the uncertainty due to sampling.…”
Section: A U T H O R C O P Ymentioning
confidence: 99%