Response rate (survey)

In survey research, response rate, also known as completion rate or return rate, is the number of people who answered the survey divided by the number of people in the sample. It is usually expressed in the form of a percentage. The term is also used in direct marketing to refer to the number of people who responded to an offer.

The general consensus in academic surveys is to choose one of the six definitions summarized by the American Association for Public Opinion Research (AAPOR). These definitions are endorsed by the National Research Council and the Journal of the American Medical Association, among other well recognized institutions. They are:

The six AAPOR definitions vary with respect to whether or not the surveys are partially or entirely completed and how researchers deal with unknown nonrespondents. Definition #1, for example, does NOT include partially completed surveys in the numerator, while definition #2 does. Definitions 3–6 deal with the unknown eligibility of potential respondents who could not be contacted. For example, there is no answer at the doors of 10 houses you attempted to survey. Maybe 5 of those you already know house people who qualify for your survey based on neighbors telling you whom lived there, but the other 5 are completely unknown. Maybe the dwellers fit your target population, maybe they don't. This may or may not be considered in your response rate, depending on which definition you use.

Example: if 1,000 surveys were sent by mail, and 257 were successfully completed (entirely) and returned, then the response rate would be 25.7%.

A survey’s response rate is the result of dividing the number of people who were interviewed by the total number of people in the sample who were eligible to participate and should have been interviewed. A low response rate can give rise to sampling bias if the nonresponse is unequal among the participants regarding exposure and/or outcome. Such bias is known as nonresponse bias.

For many years, a survey's response rate was viewed as an important indicator of survey quality. Many observers presumed that higher response rates assure more accurate survey results (Aday 1996; Babbie 1990; Backstrom and Hursh 1963; Rea and Parker 1997). But because measuring the relation between nonresponse and the accuracy of a survey statistic is complex and expensive, few rigorously designed studies provided empirical evidence to document the consequences of lower response rates until recently.

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