<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></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.

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

University of Nebraska, Department of Psychology, Lincoln, NE 68588-0308,

University of Nebraska, 2343 Stone Creek Loop South, Lincoln, NE 68512,

University of Essex, ISER, Colchester, UK CO4 3SQ.

University of Nebraska, 122E Avery Hall, Lincoln, NE 68588-0115,

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Determining which verbal behaviors of interviewers and respondents are dependent on one another is a complex problem that can be facilitated via data-mining...

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

Published Online: Sep 23, 2016

Page range: 579 - 600

Received: Apr 01, 2015

Accepted: May 01, 2016

DOI: https://doi.org/10.1515/jos-2016-0030

Keywords
Calendar interviewing, data mining, interviewing, memory aids

© 2016 Robert F. Belli et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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

Published Online: Sep 23, 2016

Page range: 579 - 600

Received: Apr 01, 2015

Accepted: May 01, 2016

DOI: https://doi.org/10.1515/jos-2016-0030

KeywordsCalendar interviewing, data mining, interviewing, memory aids

© 2016 Robert F. Belli et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
Calendar interviewing, data mining, interviewing, memory aids