Abstract #301261

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JSM 2003 Abstract #301261
Activity Number: 150
Type: Invited
Date/Time: Monday, August 4, 2003 : 2:00 PM to 3:50 PM
Sponsor: Section on Survey Research Methods
Abstract - #301261
Title: A Markovian Model for Snowball Sampling
Author(s): Naihua Duan*+ and David Kanouse
Companies: University of California, Los Angeles and RAND Corporation
Address: 10920 Wilshire Blvd., Suite 350, Los Angeles, CA, 90024-6521,
Keywords: network sampling
Abstract:

Snowball sampling is a useful technique for recruiting hidden populations or populations that are difficult to reach. A small number of members of the target population identified through massive screening or privileged contacts are used as "seeds" for recruiting additional members through referrals. It is, however, difficult to conduct statistical inference on the data collected through snowball sampling due to the selective nature of the procedures: the "seeds" might be nonrepresentative; the referrals are also likely to be non-representative. If the referral process can be sustained over multiple generations, it is conceivable that the composition of the sample will converge to a stationery distribution. We will discuss a Markovian model that allows the use of a few generations of referrals to estimate the composition of the stationery distribution, and provide inference about the target population through weight adjustment.

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