Dealing with Hard-to-Reach Populations in Panel Data: Respondent-Driven Survey (RDS) and Attrition
Hidden populations, such as irregular migrants, often elude traditional probabilistic sampling methods. In situations like these, chain-referral sampling techniques like Respondent-Driven Surveys (RDS) offer an effective solution. RDS, a variant of network sampling sometimes referred to as “snowball” sampling, estimates weights based on the network structures of friends and acquaintances formed during the sampling process. This ensures the samples are representative of the larger population. However, one significant limitation of these methods is the rigidity of the weights. When faced with participant attrition, recalibrating these weights to ensure continued representation poses a challenge. This technical note introduces a straightforward methodology to account for such attrition. Its applicability is demonstrated through a survey targeting Venezuelan migrants in Ecuador and Peru.