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

Belli, RF and Miller, LD and Al Baghal, T and Soh, L (2016) 'Using Data Mining to Predict the Occurrence of Respondent Retrieval Strategies in Calendar Interviewing: The Quality of Retrospective Reports.' Journal of Official Statistics, 32 (3). 579 - 600. ISSN 2001-7367

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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.

Item Type: Article
Uncontrolled Keywords: Calendar interviewing; data mining; interviewing; memory aids
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HA Statistics
Divisions: Faculty of Social Sciences > Institute for Social and Economic Research
Depositing User: Jim Jamieson
Date Deposited: 19 Nov 2016 12:32
Last Modified: 06 Sep 2018 12:15
URI: http://repository.essex.ac.uk/id/eprint/18083

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