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How to survey hard-to-reach populations 19 July 2011

A recent workshop organised by ISER’s Renee Luthra publicised new developments in Respondent Driven Sampling (RDS), an innovative sampling method that uses social networks to find, survey, obtain and use quantitative data that is representative of hard-to-reach populations.

The Norface and ESRC sponsored workshop brought leading statisticians working on RDS together with survey methodologists and practitioners from a variety of social science disciplines with a view to encouraging the exchange and dissemination of new findings which included the following:

Renee Luthra said:

“Governments around the world use targeted programmes designed to reach populations for which no sampling frame is present, for instance recent immigrants, drug users, homeless men and women, or individuals engaged in high risk sexual behavior. Millions of pounds are spent annually on social programmes such as those designed to aid immigrant integration, drug cessation, provide shelter, or encourage safer sex. In order to evaluate the effectiveness of such programmes, Government needs ways to survey these population members and estimate prevalence rates that are representative and unbiased. RDS presents one important sampling and estimation strategy to fulfill these needs, however, it is important that policy makers are aware of the strengths and weaknesses of the method and understand the accuracy of estimates drawn from RDS sampling and estimation designs.”

She added that there were some definite challenges surrounding RDS:

“Despite the increasing popularity of the method and considerable optimism about its potential to provide population estimates on hard to reach populations, recent research has uncovered several possible weak points in the methods, especially weaknesses in variance estimations. The accuracy of RDS is impacted by the underlying social network, the distribution of traits within this network, and the recruitment dynamic. Particular challenges are highly clustered and balkanized populations, homophily in referral chains, and the need for large samples to overcome design effects.”

RDS methods are currently used in a variety of health epidemiology settings and are sponsored by major organisations. RDS uses the social networks of hidden populations to recruit respondents. First, a few initial target population members are recruited and administered the questionnaire. These initial respondents are then trained to recruit additional members of the target population. Each respondent is provided an incentive to complete the questionnaire as well as a secondary incentive to recruit other target population members. The sample thus grows in size completely directed by respondents themselves. Population members with large social networks therefore face a higher probability of selection; to correct for this, social network data is collected and used to adjust for differential probabilities of referral.

The organisers believe the workshop has served as a first step by bringing together statisticians, survey methodologists, and researchers using RDS in an effort to disseminate knowledge and improve implementation and reporting. The resulting papers are also being prepared for review as a special issue to the Journal of the Royal Statistical Society in order to reach a wider audience.

Photo credit: pivic

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