Showing papers by "Ashton M. Verdery published in 2015"

Network Structure and Biased Variance Estimation in Respondent Driven Sampling.

Abstract: This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network.

Brief Report: Respondent-driven Sampling Estimators Under Real and Theoretical Recruitment Conditions of Female Sex Workers in China.

Abstract: We compare the performance of multiple respondent-driven sampling estimators under different sample recruitment conditions in hidden populations of female sex workers in the midst of China’s ongoing epidemic of sexually transmitted infections. We first examine empirically calibrated simulations grou

Links Between Demographic and Kinship Transitions

Abstract: The demographic transition is also a kinship transition. This insight is obvious for certain types of kin-as fertility falls parents have fewer children for instance-but its broader implications for communities remain unexplored. Prior work on this topic has focused on how the demographic transition reshapes the availability of living kin within a society over time to the neglect of how differences in the demographic transition lead to differences in kinship networks between communities. In this article I examine survey data (for rural Thailand) and use microsimulation methods to test how different pathways through the demographic transition affect kinship networks in communities. My results show that different routes through the demographic transition can substantially alter kinship network size and entirely through the mechanism of demographic change have indirect effects on community integration. These effects persist long after the demographic transition has ended. I theorize reasons that community-level differentiation in kinship networks owing to the demographic transition are an important mechanism linking the demographic transition to modernity.