We develop a method for improved estimation of a participant’s inclusion probability based on their network size (degree) as well as other information.
We revisit a novel causal model published in Demography by Hicks et al. (2018), designed to assess whether exposure to neighborhood disadvantage over time affects children's reading and math skills. Here, we provide corrected and new results. …
Respondent-driven sampling (RDS) is a method for sampling from a target population by leveraging social connections. RDS is invaluable to the study of hard-to-reach populations. However, RDS is costly and can be infeasible. RDS is infeasible when …
Respondent-driven sampling is a commonly used method for sampling from hard-to-reach human populations connected by an underlying social network of relations. Beginning with a convenience sample, participants pass coupons to invite their contacts to …
Prior research has suggested that children living in a disadvantaged neighborhood have lower achievement test scores, but these studies typically have not estimated causal effects that account for neighborhood choice. Recent studies used propensity …
Network-based models for sexually transmitted disease transmission rely on initial partnership networks incorporating structures that may be related to risk of infection. In particular, initial networks should reflect the level of concurrency and …
African-American men who have sex with men (AA MSM) have been disproportionately infected with and affected by HIV and other STIs in San Francisco and the USA. The true scope and scale of the HIV epidemic in this population has not been quantified, …
The study of hard-to-reach populations presents significant challenges. Typically, a sampling frame is not available, and population members are difficult to identify or recruit from broader sampling frames. This is especially true of populations at …
Background: Respondent-driven sampling is used worldwide to estimate the population prevalence of characteristics, such as HiV/aiDS and associated risk factors in hard-to-reach populations. estimating the total size of these populations is of great …
Respondent-Driven Sampling (RDS) is n approach to sampling design and inference in hard-to-reach human populations. It is often used in situations where the target population is rare and/or stigmatized in the larger population, so that it is …