Use of R-Indicators to Assess Survey Response Representativeness

• Activity Number: 444
• Type: Contributed
• Date/Time: Tuesday, August 6, 2013 : 2:00 PM to 3:50 PM
• Sponsor: Survey Research Methods Section
• Author(s): Jared Coopersmith*+
• Companies: Mathematica Policy Research
• Keywords: R-Indicators ; Response Rates ; Survey Representativeness

Abstract

It has been shown that response rates are inadequate for measuring response representativeness and nonresponse bias (Groves 2006; Groves and Peytcheva 2008). Further, Schouten et al. state that "subgroup response rates come closest [to supporting the data collection monitoring, targeting and prioritizing] but do not account for subgroup size, are univariate and are not available at the variable level" (2011, p.1). Recent work has led to the development of "R-indicators", which are "designed to measure the degree to which the respondents to a survey resemble the complete sample" (Schouten et al. 2011, p.232). We examine R-indicators and partial R-indicators for weekly data collection returns in order to assess the representativeness of the respondents for the 2008 and 2010 National Survey of Recent College Graduates (NSRCG), sponsored by NSF. We use sample frame data to estimate response propensities and to examine unconditional partial R-indicators. We show the overall R-indicator provides a better indicator of representativeness than the response rate and that several frame variables are disproportionately contributing to an overall lack of representativeness in the response.