Export to your Reference Manger

Please Copy & Paste



Bookmark and Share

Reduction of nonresponse bias through case prioritization

Reduktion des Nonresponsebias durch Priorisierung
[journal article]

Peytchev, Andy; Riley, Sarah; Rosen, Jeff; Murphy, Joe; Lindblad, Mark

fulltextDownloadDownload full text

(external source)

Citation Suggestion

Please use the following Persistent Identifier (PID) to cite this document:http://dx.doi.org/10.18148/srm/2010.v4i1.3037

Further Details
Abstract "How response rates are increased can determine the remaining nonresponse bias in estimates. Studies often target sample members that are most likely to be interviewed to maximize response rates. Instead, the authors suggest targeting likely nonrespondents from the onset of a study with a different protocol to minimize nonresponse bias. To inform the targeting of sample members, various sources of information can be utilized: paradata collected by interviewers, demographic and substantive survey data from prior waves, and administrative data. Using these data, the likelihood of any sample member becoming a nonrespondent is estimated and on those sample cases least likely to respond, a more effective, often more costly, survey protocol can be employed to gain respondent cooperation. This paper describes the two components of this approach to reducing nonresponse bias. The authors demonstrate assignment of case priority based on response propensity models, and present empirical results from the use of a different protocol for prioritized cases. In a field data collection, a random half of cases with low response propensity received higher priority and increased resources. Resources for high-priority cases were allocated as interviewer incentives. They find that they were relatively successful in predicting response outcome prior to the survey and stress the need to test interventions in order to benefit from case prioritization." (author's abstract)
Keywords United States of America; survey research; response behavior; error; costs; survey; estimation; data; data capture; data quality; urban sociology; statistical method; method; North America
Classification Research Design; Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Document language English
Publication Year 2010
Page/Pages p. 21-29
Journal Survey Research Methods, 4 (2010) 1
ISSN 1864-3361
Status Published Version; peer reviewed
Licence Deposit Licence - No Redistribution, No Modifications