Dennis Feehan - UC Berkeley
Using sampled social network data to estimate the size of hidden populations
Date: 10/19/2017 (Thu)
Time: 3:30pm- 5:00pm
Location: Gross Hall 270
Organizer: Scott Lynch
Meeting Schedule: Login or email the organizer to schedule a meeting.
All meetings will be in Gross Hall 230K unless otherwise noted.
8:30am - Breakfast- Jessie West, Trish Homan
9:00am - Breakfast- Jessie West, Trish Homan
9:30am - Breakfast- Jessie West, Trish Homan
10:00am - Tony Bardo
10:30am - Mark Yacoub
11:00am - OPEN
11:30am - Bryce Bartlett
12:00pm - Lunch- Emma Zang, Claire LB
12:30pm - Lunch- Emma Zang
1:00pm - Lunch- Emma Zang
1:30pm - Rob Garlick
2:00pm - Marta Mulawa
2:30pm - Lijun Song
3:00pm - Seminar Prep
3:30pm - Seminar Presentation (3:30pm to 5:00pm)
Additional Comments: Surveys have traditionally been based on the idea that researchers can estimate characteristics of a population by obtaining a sample of individuals and asking them to report about themselves. Network reporting surveys generalize this traditional approach by asking survey respondents to report about members of their personal networks. This approach can be used to study many important rare and hidden populations for which traditional survey methods are inadequate; for example, the approach has been used to estimate the size of epidemiologically important groups like sex workers, drug injectors, and men who have sex with men. It has also been used to estimate critical demographic quantities such as adult death rates. I will introduce a framework for developing estimators from network reporting surveys and then I will present some results from a nationally-representative survey experiment that my colleagues and I conducted in Rwanda.