A SIMULATION-BASED FRAMEWORK FOR ASSESSING THE FEASIBILITY OF RESPONDENT-DRIVEN SAMPLING FOR ESTIMATING CHARACTERISTICS IN POPULATIONS OF LESBIAN, GAY AND BISEXUAL OLDER ADULTS

Abstract

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 RDS point estimators have small effective sample sizes (large design effects) or when RDS interval estimators have large confidence intervals relative to estimates obtained in previous studies or poor coverage. As a result, researchers need tools to assess whether or not estimation of certain characteristics of interest for specific populations is feasible in advance. In this paper, we develop a simulation-based framework for using pilot data-in the form of a convenience sample of aggregated, egocentric data and estimates of subpopulation sizes within the target population-to assess whether or not RDS is feasible for estimating characteristics of a target population. in doing so, we assume that more is known about egos than alters in the pilot data, which is often the case with aggregated, egocentric data in practice. We build on existing methods for estimating the structure of social networks from aggregated, egocentric sample data and estimates of subpopulation sizes within the target population. We apply this framework to assess the feasibility of estimating the proportion male, proportion bisexual, proportion depressed and proportion infected with HIV/AIDS within three spatially distinct target populations of older lesbian, gay and bisexual adults using pilot data from the caring and Aging with Pride Study and the Gallup Daily Tracking Survey. We conclude that using an RDS sample of 300 subjects is infeasible for estimating the proportion male, but feasible for estimating the proportion bisexual, proportion depressed and proportion infected with HIV/AIDS in all three target populations.

Keywords: Respondent-driven sampling; aggregated egocentric sample data; hard to reach populations; network sampling; social networks.

Fig. 1.

Social network questions in the CAP questionnaire.

Fig. 2.

Estimates of the proportion bisexual by gender and age group θ for each MSA. Dashed bars represent standard errors.

Fig. 3.

Estimates of degree distributions by gender and age group constructed from estimates of negative binomial parameters ρ and π. Different line types correspond to different age groups and gender identities.

Fig. 4.

Estimates of mixing parameters α. For each estimated mixing parameter ${\widehat{\alpha }}_{ij}$, i is indexed on the horizontal axis and j is indexed by color. For instance, the estimate ${\widehat{\alpha }}_{\mathcal{GW},\mathcal{GW}}$, is given by the first bar from the left in first panel. α_ij = 1 reflects no preferential mixing, that is, egos of type i are as likely to have alters of type j as alters of other types. ∣α_ij ∣ > 1 indicates preferential mixing, that is, egos of type i are more or less likely to have alters of type j than other types. Dashed bars represent standard errors.