Department of Biostatistics
Statistical Methods in Epidemiology Working Group
2015 - 2016
ABSTRACT: We propose a network method to monitor health behaviors and point out the general conditions for it to work effectively. The method helps to identify effective informants for monitoring future health behaviors and to triangulate self-reports of sensitive health behaviors. We demonstrate the method by studying the smoking behaviors of over 4000 middle school students in China. Using students' observations of their schoolmates smoking in the past 30 days, we construct smoking detection networks and examine the patterns of smoking detection through exponential random graph models. We find that smokers, optimistic students, and popular students make better informants than their counterparts. We also find that using three to four (or the 3rd quartile of) positive peer reports can uncover a good number of under-reported smokers while not producing excessive false positives. In short, the method we proposed may be used to improve future survey designs and data quality with a low cost.
|Back to SPH Biostatistics||
Maintained by the
Last Update: September 18, 2015