EVALUATION OF THE EFFECT OF DEGREE DISTRIBUTION ON RESPONDENT-DRIVEN SAMPLING (RDS) ESTIMATOR AMONG INJECTION DRUG USERS

Abstract

The Respondent-driven sampling (RDS) method has become a successful approach for recruiting hard-to-reach populations, leading to a significant rise in its use worldwide. However, making reliable inferences from RDS data poses challenges due to assumptions associated with its statistical methodology. Most studies focus on population prevalence estimates but often neglect the network size(degree). This study used simulations and real-world data to examine the effects of degree distributions in networked populations, aiming to evaluate the