JSM 2005 - Toronto

Abstract #304549

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 392
Type: Topic Contributed
Date/Time: Wednesday, August 10, 2005 : 10:30 AM to 12:20 PM
Sponsor: Section on Survey Research Methods
Abstract - #304549
Title: Detecting and Accounting for Clustering in Data from Time-space Sample (TSS) Surveys
Author(s): John Karon*+
Companies: Emergint Corporation
Address: 2505 Elfego Road, Albuquerque, NM, 87107-3010, United States
Keywords: sample survey ; multiplicity ; time-space sampling ; hard-to-reach population ; gay men ; HIV
Abstract:

As part of National HIV Behavioral Surveillance (NHBS), CDC has conducted TSS surveys of men who have sex with men (MSM). TSS designs are used to collect data from hard-to-reach populations. Venues are chosen from a sampling frame of venues at which persons in the population can be found. A time period is defined for each venue and persons attending during this period are sampled. In the Young Men's Study Phase II, a TSS survey of MSM, design effects within cities for estimates of proportions are < 1 to 7.6. Binomial confidence intervals for the observed proportions under the hypothesis of no clustering help identify venues responsible for clustering. A random-effects model provides a formal test for clustering. If everyone in the population has the same pattern of choosing both a venue in the frame and a time period, given the person attends some venue in the frame, an appropriate sampling weight is the inverse of the probability that the person attends some venue in the frame on a given day. Data on frequency of attendance at venues in the frame should be collected and used to compute analysis weights. Clustering must be considered for a correct variance estimate.

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Revised March 2005