Abstract
This article develops a two-stage statistical analysis to identify and assess the effect of a sample bias associated with an individual’s household role. Survey responses to questions about the respondent’s role in household finances and a sampling design in which some households have all members take the survey enable the estimation of distributions for each individual’s share of household responsibility. The methodology is applied to the 2017 Survey of Consumer Payment Choice. The distribution of responsibility shares among survey respondents suggests that the sampling procedure favors household members with higher levels of responsibility. A bootstrap analysis reveals that population mean estimates of monthly payment instrument use that do not account for this type of sample misrepresentation are likely biased for instruments often used to make household purchases. For checks and electronic payments, our analysis suggests that it is likely that unadjusted estimates overstate true values by 10–20 percent.
Comparing sample bias correction methods for species distribution modeling using virtual species