Print  Close

Assessing Data Quality and Inference in a Web Respondent Driven Sampling Study of Ethnic Minorities

Abstract Number:

3668 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Paper 

Participants:

Kaidar Nurumov (1), Sunghee Lee (1)

Institutions:

(1) University of Michigan, N/A

Co-Author:

Sunghee Lee  
University of Michigan

First Author:

Kaidar Nurumov  
University of Michigan

Presenting Author:

Kaidar Nurumov  
N/A

Abstract Text:

Web-based respondent driven sampling (W-RDS), an application of RDS, has potential to recruit hard-to-reach groups with strong social ties and a high Web access rate, such as certain racial/ethnic minority groups. However, little is known about the quality of W-RDS data and the performance of popular RDS estimators.
This study attempts to fill this gap with a national W-RDS study of Korean Americans, Health and Well-being of Koreans (HAWK). This study experimented on the seed types recruited from two sources: 1) social media; and 2) randomly selected addresses in the commercial data associated with Korean surnames. We will compare the HAWK sample estimates by seed type and against estimates for Korean Americans from the American Community Survey. In doing so, we will apply existing RDS estimators as well as model-based estimators to the HAWK data.

Keywords:

Respondent Driven Sampling|Web Survey|Statistical inference|Data quality|Model-based estimators|RDS estimators

Sponsors:

Survey Research Methods Section

Tracks:

Non-probability Samples

Can this be considered for alternate subtype?

Yes

Are you interested in volunteering to serve as a session chair?

No

I have read and understand that JSM participants must abide by the Participant Guidelines.

Yes

I understand that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is non-refundable.

I understand