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Association: Name: American Association for Public Opinion Research URL: http://www.aapor.org
Citation: URL: http://www.allacademic.com/meta/p116308_index.html Direct Link: HTML Code:

Krosnick, Jon., Miller, Joanne. and Wedeking, Justin. "Data Quality of Refusal Conversions and Call-Backs" Paper presented at the annual meeting of the American Association for Public Opinion Research, Sheraton Music City, Nashville, TN, Aug 16, 2003 <Not Available>. 2009-05-26 <http://www.allacademic.com/meta/p116308_index.html>

Krosnick, J. A., Miller, J. M. and Wedeking, J. , 2003-08-16 "Data Quality of Refusal Conversions and Call-Backs" Paper presented at the annual meeting of the American Association for Public Opinion Research, Sheraton Music City, Nashville, TN <Not Available>. 2009-05-26 from http://www.allacademic.com/meta/p116308_index.html

Publication Type: Conference Paper/Unpublished Manuscript Review Method: Peer Reviewed Abstract: Survey researchers expend tremendous effort attempting to maximize response rates. Two important methods for maximizing response rates are refusal conversions and call-backs. Whereas obtaining high rates of refusal conversions and high rates of compliance from people who are difficult to contact by telephone does, in fact, increase response rates, this may be at the expense of data quality. For example, people who initially refuse to be interviewed are later recontacted by an experienced interviewer who attempts to inspire compliance. If these individuals do agree to be interviewed, they may be especially likely to satisfice, rather than optimize, when answering questions. Thus, the quality of their data may be low enough to undermine the value of their participation. With regard to call-backs, difficult-to-contact respondents may or may not produce systematic changes in the composition of a sample, or the reports they provide, depending on whether or not contactibility is essentially a random function of people's busy schedules. Analyzing data from a series of state-wide and national surveys, we explore whether respondents interviewed only after initial refusal or after many contact attempts provide answers systematically different, in ways that may increase or decrease data quality, from quickly contacted and immediately cooperative respondents.

The Impact of Providing Incentives to Initial Refusal Cases on Sample Composition and Data Quality in a Telephone Survey

Does “Call Me Back Later” Really Mean “I Refuse”? An Experiment to Convert Soft Refusals in a Business Survey

Measuring Public Opinion: Examining the Impact of Refusal Conversions and Callbacks on Data Quality