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Author ORCID Identifier

https://orcid.org/ 0000-0002-3540-8255

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AccessType

Open Access Dissertation

Document Type

dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Public Health

Year Degree Awarded

2022

Month Degree Awarded

September

First Advisor

Leontine Alkema

Second Advisor

Antoine Chambaz

Third Advisor

Laura Balzer

Subject Categories

Biostatistics

Abstract

The international community via the United Nations Sustainable Development Goals has set the target of universal access to reproductive health-care services, including family planning, by 2030. Progress towards reaching this goal is assessed by tracking appropriate demographic and health indicators at national and subnational levels. This task is challenging, however, in populations where relevant data are limited or of low quality. Statistical models are then needed to estimate and project demographic and health indicators in populations based on the available data. Our first contribution, in Chapter 1, is to unify many existing demographic and health indicator models by proposing an overarching model class, Temporal Models for Multiple Populations. In Chapter 2, we focus on the Modern Contraceptive Prevalence Rate (mCPR) indicator, which we model at the national level with a novel Bayesian method based on B-splines. Finally, in Chapter 3 we turn to the problem of defining and estimating the effect of interventions on family planning behavior using a novel targeted Bayesian estimator for Marginal Structural Models.

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DOI

https://doi.org/10.7275/30431180

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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Biostatistics Commons

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