Respondent Driven Sampling (RDS)

Respondent driven sampling (RDS) is a sampling method utilized worldwide in surveys among "hard to reach" socially networked populations. RDS is a type of chain referral sampling which is useful in situations whereby traditional probability sampling methods are infeasible. RDS uses several theoretical premises borrowed from sociological statistics to mitigate the biases associated with chain referral sampling. Specifically, RDS utilizes a branch of social science known as social network theory. Social network theory attempts to map relationships and characteristics shared by groups. Information about the social networks of persons recruited into an RDS survey are used to determine the probability of each recruits selection and to mitigate the biases associated with over or under sampling certain groups. 

RDS recruitment is initiated with a small, diverse and influential group of “seeds" (eligible respondents) selected by the researchers. Each seed receives a set number of recruitment coupons to recruit his/her peers who then present the coupons at a fixed site to enroll in the survey. Eligible recruits who finish the survey process are also given a set number of coupons to recruit their peers. The recruited peers of seeds who enroll in the survey become wave one respondents, and the recruits of wave one respondents become wave two respondents. This process of recruitment continues through successive waves until the calculated sample size is reached. In the end, the waves produced by effective seeds make up recruitment chains of varying lengths. The goal is to acquire long recruitment chains made up of multiple waves. In the figure below, there are four seeds (in black) and a maximum of 10 waves in one of the chains. For more information on RDS methods, see the RDS manual I wrote for the World Health Organization.