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Occupation Coding during the Interview in a Web-First Sequential Mixed-Mode Survey

Peycheva, DN; Sakshaug, JW; Calderwood, L; (2021) Occupation Coding during the Interview in a Web-First Sequential Mixed-Mode Survey. Journal of Official Statistics , 37 (4) pp. 981-1007. 10.2478/jos-2021-0042. Green open access

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Abstract

Coding respondent occupation is one of the most challenging aspects of survey data collection. Traditionally performed manually by office coders post-interview, previous research has acknowledged the advantages of coding occupation during the interview, including reducing costs, processing time and coding uncertainties that are more difficult to address post-interview. However, a number of concerns have been raised as well, including the potential for interviewer effects, the challenge of implementing the coding system in a web survey, in which respondents perform the coding procedure themselves, or the feasibility of implementing the same standardized coding system in a mixed-mode self- A nd interviewer-administered survey. This study sheds light on these issues by presenting an evaluation of a new occupation coding method administered during the interview in a large-scale sequential mixed-mode (web, telephone, face-to-face) cohort study of young adults in the UK. Specifically, we assess the take-up rates of this new coding method across the different modes and report on several other performance measures thought to impact the quality of the collected occupation data. Furthermore, we identify factors that affect the coding of occupation during the interview, including interviewer effects. The results carry several implications for survey practice and directions for future research.

Type: Article
Title: Occupation Coding during the Interview in a Web-First Sequential Mixed-Mode Survey
Open access status: An open access version is available from UCL Discovery
DOI: 10.2478/jos-2021-0042
Publisher version: https://doi.org/10.2478/jos-2021-0042
Language: English
Additional information: © 2020 Darina N. Peycheva et al., published by Sciendo This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License (https://creativecommons.org/licenses/by-nc-nd/3.0/).
UCL classification: UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education
UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Social Research Institute
UCL > Provost and Vice Provost Offices > School of Education
UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10142716
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