Studies of Welfare Populations: Data Collection and Research Issues. Response Rates on RDD Surveys

06/01/2002

To provide some perspective on the level of response achieved on RDD surveys, Massey et al. (1998) presented results of a study that reviewed the response rates of a large number of RDD surveys conducted for government agencies or as part of a large survey effort. Their results found a median response rate 60 to 64 percent with about 20 percent of the surveys exceeding 70 percent. The overall perception among survey analysts is that the trend is for this rate to decrease over time. That is, achieving high response rates for RDD surveys is becoming more difficult.

An RDD survey of low-income populations faces several hurdles relative to achieving a high response rate. The first is the need to screen all households on the basis of income. This leads to two types of problems. The first is that it adds an opportunity for someone to refuse to do the survey. A screener written to find low-income households has to include a number of questions that respondents are sensitive to, including information on who lives in the households, and some type of income measure. Much of the nonresponse on RDD surveys occur at this point in the process. For example, on the NSAF, a national RDD survey that over-samples low-income groups, the screener response rate was in the high 70s. Once a respondent within the household was selected, the response rate to do the extended interview was in the 80s. Nonetheless, the combination of the two rates, which form the final response rate, resulted in a rate in the mid-60s (Brick et al., 1999).

Low response rates on RDD surveys are partly an issue of credibility. Relative to a survey of welfare leavers, the issue of credibility places more emphasis on design features that motivate respondents to participate in the survey (vis-à-vis trying to locate respondents). For example, research on methods to increase RDD response rates has shown that prenotification prior to the call, methods of delivery of prenote letters, and use of incentives can provide important boosts above those normally achieved when implementing many of the other important design features reviewed earlier. All three of these increase response rates in the context of an RDD survey (Camburn et al., 1995; Brick et al., 1997; Cantor et al, 1999).

In addition, refusal conversion is particularly important for an RDD survey, because such a large proportion of the nonresponse is from refusals. Refusal to the screener could be from almost any member of the household, because most screeners accept responses from any adult who answers the phone. Calling the household a second time provides an opportunity to obtain another person in the household (who may be more willing to participate) or reach the same respondent who may not be as difficult to convince to participate in a short screening instrument. Refusal to the extended interview may be more difficult to turn around. Refusal conversion strategies at this level are amenable to more traditional tailoring methods (e.g., Groves and Couper, this volume: Chapter 1), because respondents at this stage of the process may be more willing to listen to the interviewer.

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