# Estimating adult death rates from sibling histories: A network approach

## TL;DR

This paper introduces a network-based statistical framework for analyzing sibling survival data to estimate adult mortality in countries lacking complete death registration, along with an R package implementation.

## Contribution

It re-frames the sibling survival method as a network sampling problem, providing formal estimators and consistency checks for mortality estimates.

## Key findings

- Derived statistical estimators for sibling survival data
- Clarified conditions for accurate sibling history estimates
- Developed internal consistency checks for data quality

## Abstract

Hundreds of millions of people live in countries that do not have complete death registration systems, meaning that most deaths are not recorded and critical quantities like life expectancy cannot be directly measured. The sibling survival method is a leading approach to estimating adult mortality in the absence of death registration. The idea is to ask a survey respondent to enumerate her siblings and to report about their survival status. In many countries and time periods, sibling survival data are the only nationally-representative source of information about adult mortality. Although a huge amount of sibling survival data has been collected, important methodological questions about the method remain unresolved. To help make progress on this issue, we propose re-framing the sibling survival method as a network sampling problem. This approach enables us to formally derive statistical estimators for sibling survival data. Our derivation clarifies the precise conditions that sibling history estimates rely upon; it leads to internal consistency checks that can help assess data and reporting quality; and it reveals important quantities that could potentially be measured to relax assumptions in the future. We introduce the R package siblingsurvival, which implements the methods we describe.