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Combining Survey and Census Data in ...

Wilson, Katherine.

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Combining Survey and Census Data in Time and Space in a Developing World Context.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Combining Survey and Census Data in Time and Space in a Developing World Context./
Author:	Wilson, Katherine.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	174 p.
Notes:	Source: Dissertations Abstracts International, Volume: 80-10, Section: B.
Contained By:	Dissertations Abstracts International80-10B.
Subject:	Biostatistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13809684
ISBN:	9781392070697

Combining Survey and Census Data in Time and Space in a Developing World Context.
Wilson, Katherine.

Combining Survey and Census Data in Time and Space in a Developing World Context. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 174 p.

Source: Dissertations Abstracts International, Volume: 80-10, Section: B.

Thesis (Ph.D.)--University of Washington, 2019.

This item must not be added to any third party search indexes.

Obtaining reliable estimates of health indicators at a granular level in space and time is important for informing health intervention and public policy decisions. In low and middle income countries, the data available come from a multitude of sources including vital registration systems, complex surveys, and disease registries. These data sources are often of varying quality. In particular, the information on health outcomes may be aggregated over space and time. Overall, this poses a modeling challenge as there is a mismatch between the underlying process, the observed data, and the inferential resolution desired. This work tackles three main issues that are commonly faced in this setting by developing Bayesian models tailored to the specific problem at hand. In particular, this work considers incorporating data where the outcome has been aggregated over space (common in census data), the outcome is associated with a point in space but the exact location is unknown (common in household survey data), and the outcome has been aggregated over time (common in modeling child mortality using census data).

ISBN: 9781392070697Subjects--Topical Terms:

1002712
Biostatistics.

Combining Survey and Census Data in Time and Space in a Developing World Context.
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300 $a 174 p.
500 $a Source: Dissertations Abstracts International, Volume: 80-10, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Wakefield, Jon.
502 $a Thesis (Ph.D.)--University of Washington, 2019.
506 $a This item must not be added to any third party search indexes.
506 $a This item must not be sold to any third party vendors.
520 $a Obtaining reliable estimates of health indicators at a granular level in space and time is important for informing health intervention and public policy decisions. In low and middle income countries, the data available come from a multitude of sources including vital registration systems, complex surveys, and disease registries. These data sources are often of varying quality. In particular, the information on health outcomes may be aggregated over space and time. Overall, this poses a modeling challenge as there is a mismatch between the underlying process, the observed data, and the inferential resolution desired. This work tackles three main issues that are commonly faced in this setting by developing Bayesian models tailored to the specific problem at hand. In particular, this work considers incorporating data where the outcome has been aggregated over space (common in census data), the outcome is associated with a point in space but the exact location is unknown (common in household survey data), and the outcome has been aggregated over time (common in modeling child mortality using census data).
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650 4 $a Public health. $3 534748
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773 0 $t Dissertations Abstracts International $g 80-10B.
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