Estimating and Correcting Degree Ratio Bias in the Network Scale-up Method

Fuente: arXiv
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Bibliographic Details
Main Authors: Laga, Ian, Kunke, Jessica P., McCormick, Tyler H., Niu, Xiaoyue
Format: Preprint
Published: 2023
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author Laga, Ian
Kunke, Jessica P.
McCormick, Tyler H.
Niu, Xiaoyue
author_facet Laga, Ian
Kunke, Jessica P.
McCormick, Tyler H.
Niu, Xiaoyue
contents The Network Scale-up Method (NSUM) uses social networks and answers to "How many X's do you know?" questions to estimate sizes of groups excluded by standard surveys. This paper addresses the bias caused by varying average social network sizes across populations, commonly referred to as the degree ratio bias. This bias is especially important for marginalized populations like sex workers and drug users, where members tend to have smaller social networks than the average person. We show how the degree ratio affects size estimates and provide a method to estimate degree ratios without collecting additional data. We demonstrate that our adjustment procedure improves the accuracy of NSUM size estimates using simulations and data from two data sources.
format Preprint
id arxiv_https___arxiv_org_abs_2305_04381
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Estimating and Correcting Degree Ratio Bias in the Network Scale-up Method
Laga, Ian
Kunke, Jessica P.
McCormick, Tyler H.
Niu, Xiaoyue
Applications
The Network Scale-up Method (NSUM) uses social networks and answers to "How many X's do you know?" questions to estimate sizes of groups excluded by standard surveys. This paper addresses the bias caused by varying average social network sizes across populations, commonly referred to as the degree ratio bias. This bias is especially important for marginalized populations like sex workers and drug users, where members tend to have smaller social networks than the average person. We show how the degree ratio affects size estimates and provide a method to estimate degree ratios without collecting additional data. We demonstrate that our adjustment procedure improves the accuracy of NSUM size estimates using simulations and data from two data sources.
title Estimating and Correcting Degree Ratio Bias in the Network Scale-up Method
topic Applications
url https://arxiv.org/abs/2305.04381