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ISSN: 2333-9721
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-  2019 

The Evaluation of Statistical Process Control Methods to Monitor Interview Duration During Survey Data Collection

DOI: 10.1177/2158244019854652

Keywords: interview duration,multiple regression model,statistical process control

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Abstract:

Despite general agreement regarding the usefulness of statistical process control (SPC) tools for monitoring paradata, using SPC from an early phase of the survey fieldwork is rather rare. This study focuses on one type of paradata—interview duration—to fill this void. First, we establish a procedure based on the idea of enabling fieldwork monitoring for the seventh round of the European Social Survey in Belgium from its start. The impact of respondent characteristics on interview duration is controlled for by multiple regression. Moreover, we simulate the real conditions of an ongoing survey data collection process by cumulating data and repeating the identification of problematic interviews each week, on the basis that “new” data are available. Second, for each interview we record and track the results with regard to whether or not it is problematic over the fieldwork period, to examine the consistency of our findings. We find that as more data becomes available, the results concerning whether an interview is problematic changes in only 0.3% of the cases. Out of the 27 interviews identified as problematic when all information was available, 25 were immediately identified once relevant information was available. Overall, these findings suggest that SPC tools are reliable and efficient in a survey context, and accordingly have great potential for allowing survey practitioners to focus on the interviews for which further examination is needed immediately, rather than when the data collection has been completed

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