Using Data Mining to Predict the Occurrence of Respondent Retrieval Strategies in Calendar Interviewing: The Quality of Retrospective Reports

Belli Robert F. (), Miller L. Dee (), Baghal Tarek Al () and Soh Leen-Kiat ()
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Belli Robert F.: University of Nebraska, Department of Psychology, Lincoln, NE 68588-0308, United States of America
Miller L. Dee: University of Nebraska, 2343 Stone Creek Loop South, Lincoln, NE 68512, United States of America
Baghal Tarek Al: University of Essex, ISER, Colchester, UK CO4 3SQ.
Soh Leen-Kiat: University of Nebraska, 122E Avery Hall, Lincoln, NE 68588-0115, United States of America

Journal of Official Statistics, 2016, vol. 32, issue 3, 579-600

Abstract: Determining which verbal behaviors of interviewers and respondents are dependent on one another is a complex problem that can be facilitated via data-mining approaches. Data are derived from the interviews of 153 respondents of the Panel Study of Income Dynamics (PSID) who were interviewed about their life-course histories. Behavioral sequences of interviewer-respondent interactions that were most predictive of respondents spontaneously using parallel, timing, duration, and sequential retrieval strategies in their generation of answers were examined. We also examined which behavioral sequences were predictive of retrospective reporting data quality as shown by correspondence between calendar responses with responses collected in prior waves of the PSID. The verbal behaviors of immediately preceding interviewer and respondent turns of speech were assessed in terms of their co-occurrence with each respondent retrieval strategy. Interviewers’ use of parallel probes is associated with poorer data quality, whereas interviewers’ use of timing and duration probes, especially in tandem, is associated with better data quality. Respondents’ use of timing and duration strategies is also associated with better data quality and both strategies are facilitated by interviewer timing probes. Data mining alongside regression techniques is valuable to examine which interviewer-respondent interactions will benefit data quality.

Keywords: Calendar interviewing; data mining; interviewing; memory aids (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:32:y:2016:i:3:p:579-600:n:2

DOI: 10.1515/jos-2016-0030

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