Investigating call record data using sequence analysis
Investigating call record data using sequence analysis
Researchers have become increasingly interested in better understanding the survey data collection process in interviewer-administered surveys. However, tools for analysing paradata capturing information about field processes, also called call record data, are still not yet fully explored. This paper introduces sequence analysis as a simple tool for investigating such data with the aim of better understanding survey processes and improving survey monitoring. Combining the technique with optimal matching, clustering and multidimensional scaling, the method offers a way of visualising and summarising complex call record data. A novel approach is to use sequence analysis within interviewers, which allows the identification of unusual interviewer calling behaviours, and may provide guidance on interviewer performance. The method may hence be informative for adaptive survey designs and will help to identify unusual behaviour and outliers. The technique is applied to call record data from the UK Understanding Society survey. The findings inform further modelling of call record data to increase efficiency in call scheduling and for the improvement of call outcome predictions.
37-54
Durrant, Gabriele
14fcc787-2666-46f2-a097-e4b98a210610
Maslovskaya, Olga
9c979052-e9d7-4400-a657-38f1f9cd74d0
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
Durrant, Gabriele
14fcc787-2666-46f2-a097-e4b98a210610
Maslovskaya, Olga
9c979052-e9d7-4400-a657-38f1f9cd74d0
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
Durrant, Gabriele, Maslovskaya, Olga and Smith, Peter W.F.
(2018)
Investigating call record data using sequence analysis.
International Journal of Social Research Methodology, .
(doi:10.1080/13645579.2018.1490981).
Abstract
Researchers have become increasingly interested in better understanding the survey data collection process in interviewer-administered surveys. However, tools for analysing paradata capturing information about field processes, also called call record data, are still not yet fully explored. This paper introduces sequence analysis as a simple tool for investigating such data with the aim of better understanding survey processes and improving survey monitoring. Combining the technique with optimal matching, clustering and multidimensional scaling, the method offers a way of visualising and summarising complex call record data. A novel approach is to use sequence analysis within interviewers, which allows the identification of unusual interviewer calling behaviours, and may provide guidance on interviewer performance. The method may hence be informative for adaptive survey designs and will help to identify unusual behaviour and outliers. The technique is applied to call record data from the UK Understanding Society survey. The findings inform further modelling of call record data to increase efficiency in call scheduling and for the improvement of call outcome predictions.
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Accepted/In Press date: 15 June 2018
e-pub ahead of print date: 19 September 2018
Identifiers
Local EPrints ID: 421911
URI: http://eprints.soton.ac.uk/id/eprint/421911
ISSN: 1364-5579
PURE UUID: b0a05d1e-a065-4e8f-8f94-748315ce6a9c
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Date deposited: 09 Jul 2018 16:30
Last modified: 18 May 2024 04:01
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