Have a personal or library account? Click to login
Occupation Coding During the Interview in a Web-First Sequential Mixed-Mode Survey Cover

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

Open Access
|Dec 2021

References

  1. Belloni, M., A. Brugiavini, E. Meschi, and K. Tijdens. 2016. “Measuring and detecting errors in occupational coding: an analysis of SHARE data.” Journal of Official Statistics, 32(4): 917–945. DOI: https://doi.org/10.1515/jos-2016-0049.10.1515/jos-2016-0049
  2. Bergmann, M.M., and D. Joye. 2005. “Comparing Social Stratification Schemata: CAMSIS, CSP-CH, Goldthorpe, ISCO-88, Treiman, and Wright.” Cambridge Studies in Social Research 10: 1–35. Available at: https://www.sociology.cam.ac.uk/system/-files/documents/cs10.pdf (accessed October 2019).
  3. Brugiavini, A., M. Belloni, R.E. Buia, and M. Martens. 2017. The “Job Coder”. In SHARE Wave 6: Panel innovations and collecting Dried Blood Spots. Edited by F. Malter and A. Börsch-Supan. Munich: MEA, Max Planck Institute for Social Law and Social Policy: 51–70. Available at: http://www.share-project.org/uploads/tx_sharepublications/201804_SHARE-WAVE-6_MFRB.pdf (accessed October 2019).
  4. Burstyn, I., A. Slutsky, D.G. Lee, A.B. Singer, Y. An, and Y.L. Michael. 2014. “Beyond Crosswalks: Reliability of Exposure Assessment Following Automated Coding of FreeText Job Descriptions for Occupational Epidemiology.” The Annals of Occupational Hygiene 58(4): 482–492. DOI: https://doi.org/10.1093/annhyg/meu006.10.1093/annhyg/meu00624504175
  5. Campanelli, P., K. Thompson, N. Moon, and T. Staples. 1997. “The Quality of Occupational Coding in the United Kingdom.” In Survey Measurement and Process Quality. Edited by L. Lyberg, P. Biemer, M. Collins, E. De Leeuw, C. Dippo, N. Schwarz, and D. Trewin: 437–453. New York: Wiley.
  6. Cantor, D., and J.L. Esposito. 1992. “Evaluating Interviewer Style for Collecting Industry and Occupation Information.” In Proceedings of the Section on Survey Methods, American Statistical Association: 661–666. Available at https://www.bls.gov/osmr/research-papers/1992/pdf/cp920010.pdf (accessed March 2021).
  7. Centre for Longitudinal Studies. 2017. Next Steps Age 25 Survey. Technical Report. University College London. Available at: http://doc.ukdataservice.ac.uk/doc/5545/mrdoc/pdf/5545age_25_technical_report.pdf (accessed October 2019).
  8. Conrad, F., M. Couper, and J.W. Sakshaug. 2016. “Classifying Open-Ended Reports: Factors Affecting the Reliability of Occupation Codes.” Journal of Official Statistics 32(1): 75–92. DOI: https://doi.org/10.1515/jos-2016-0003.10.1515/jos-2016-0003
  9. Creecy, R.H., B.M. Masand, S.J. Smith, and D.L. Waltz. 1992. “Trading MIPS and memory for knowledge engineering”. Communications of the ACM 35(8): 48–64. DOI: https://doi.org/10.1145/135226.135228.10.1145/135226.135228
  10. Department for Education. 2011. LSYPE User Guide to the Datasets: Wave 1 to Wave 7. Available at: http://doc.ukdataservice.ac.uk/doc/5545/mrdoc/pdf/5545lsype_user_guide_wave_1_to_wave_7.pdf (accessed October 2019).
  11. Elias, P., M. Birch, and R. Ellison. 2014. CASCOT International version 5. User Guide. Institute for Employment Research, University of Warwick, Coventry. Available at: https://warwick.ac.uk/fac/soc/ier/software/cascot/internat/cascot_international_user_-guide.pptx (accessed October 2019).
  12. Gweon H., M. Schonlau, L. Kaczmirek, M. Blohm, and S. Steiner. 2017. “Three Methods for Occupation Coding Based on Statistical Learning.” Journal of Official Statistics 33(1): 101–122. DOI: http://dx.doi.org/10.1515/JOS-2017-0006.10.1515/jos-2017-0006
  13. Hacking, W., J. Michiels, and S. Jansen, S. 2006. “Computer Assisted Coding by Interviewers.” In Proceedings of the 10th International Blaise Users Conference, IBUC 2006, 9–12 May, Arnhem, The Netherlands. Available at: http://blaiseusers.org/2006/Papers/291.pdf (accessed October 2019).
  14. Helppie-McFall, B. and A. Sonnega. 2018. Feasibility and Reliability of Automated Coding of Occupation in the Health and Retirement Study. Ann Arbor MI: University of Michigan Retirement Research Center (WP 2018-392). Available at: https://mrdrc.isr.umich.edu/publications/papers/pdf/wp392.pdf (accessed October 2020).10.2139/ssrn.3338502
  15. Hoffman, E. 1995. What Kind of Work Do You Do? Data collection and processing strategies when measuring “occupation” for statistical surveys and administrative records. ILO. (WP 1995: 95-1). Available at: https://www.ilo.org/wcmsp5/groups/public/–-dgreports/–-stat/documents/publication/wcms_087880.pdf (accessed October 2019).
  16. Hox, J.J., E.D. De Leeuw, and E.A. Zijlmans. 2015. “Measurement Equivalence in Mixed Mode Surveys.” Frontiers in Psychology 6(87): 1–11. DOI: https://doi.org/10.3389/fpsyg.2015.00087.10.3389/fpsyg.2015.00087431828225699002
  17. Klausch, T., B. Schouten, and J.J. Hox. 2017. “Evaluating Bias of Sequential Mixed-Mode Designs against Benchmark Surveys,” Sociological Methods and Research 46(3): 456–489. DOI: https://doi.org/10.1177/0049124115585362.10.1177/0049124115585362
  18. Lyberg, L., and P. Dean. 1992. Automated Coding of Survey Responses: An International Review. R&D Reports (1992–2). Statistics Sweden, Stockholm, Sweden. Available at: https://www.scb.se/contentassets/7c4edb581f8745e3a081e1ba9b332eb4/rnd-report-1992-02-green.pdf (accessed October 2019).
  19. Massing, N., M. Wasmer, C. Wolf, and C. Zuell. 2019. “How Standardized is Occupational Coding? A Comparison of Results from Different Coding Agencies in Germany.” Journal of Official Statistics 35(1): 167–187. DOI: http://dx.doi.org/10.2478/JOS-2019-0008.10.2478/jos-2019-0008
  20. Office for National Statistics. 2010a. Standard Occupational Classification 2010 Volume 1 Structure and descriptions of unit groups. Available at: https://www.ons.gov.uk/-methodology/classificationsandstandards/standardoccupationalclassificationsoc/-soc2010/soc2010volume1structureanddescriptionsofunitgroups (accessed October 2019).
  21. Office for National Statistics. 2010b. Standard Occupational Classification 2010 Volume 2: the structure and coding index. Available at: https://www.https://www.ons.gov.uk/-methodology/classificationsandstandards/standardoccupationalclassificationsoc/-soc2010/soc2010volume2thestructureandcodingindex (accessed October 2020).
  22. Ossiander, E.M., and S. Milham. 2006. “A computer system for coding occupation.” American Journal of Industrial Medicine 49: 854–857. DOI: https://doi.org/10.1002/ajim.20355.10.1002/ajim.2035516804909
  23. Schierholz, M., M. Gensicke, N. Tschersich, and F. Kreuter. 2018. “Occupation Coding During the Interview.” Journal of the Royal Statistical Society A 181: 379–407. DOI: http://dx.doi.org/10.1111/rssa.12297.10.1111/rssa.12297
  24. Schierholz, M., and M. Schonlau. 2020. “Machine Learning for Occupation Coding – a Comparison Study.” Journal of Survey Statistics and Methodology, smaa023. DOI: https://doi.org/10.1093/jssam/smaa023.10.1093/jssam/smaa023
  25. Tijdens, K. 2014. Reviewing the measurement and comparison of occupations across Europe (WP 149, AIAS). Available at: https://pure.uva.nl/ws/files/2172301/154005_WP149_Tijdens_1.pdf (accessed October 2019).
  26. Tijdens, K. 2015a. The design of a tool for the measurement of occupations in web surveys using a global index of occupations. Leuven. (WP InGRID project M21.2). Available at: https://inclusivegrowth.be/downloads/output/m21-4-coding-tool-eind.pdf (accessed October 2020).
  27. Tijdens, K. 2015b. “Self-identification of occupation in web surveys: requirements for search trees and look-up tables” Survey Methods: Insights from the Field. Available at: https://surveyinsights.org/wp-content/uploads/2015/06/Self-identification-of-occupation-in-web-surveys-requirements-for-search-trees-and-look-up-tables-Survey-Methods-Insights-from-the-Field-SMIF.pdf (accessed October 2020).
  28. Tijdens, K. 2016. “Measuring occupations: respondent’s self- identification from a large database.” In Proceedings of European Conference on Quality of Official Statistics, Special session: Synergies for Europe’s Research Infrastructures in the Social Sciences and Official Statistics (SERISS), 2 June 2016. Available at: https://seriss.eu/wp-content/uploads/2016/06/Measuring-Occupations-Respondent%e2%80%99s-self-identification-from-a-large-database.pdf (accessed October 2020).
  29. Tijdens, K., and S. Visintin. 2017. EU-harmonised and comparative measurement of occupations and skills. Leuven. (InGRID project Deliverable 21.1). Available at: https://inclusivegrowth.be/downloads/output/d21-1-eind.pdf (accessed October 2019).
  30. Vannieuwenhuyze, J.T.A., and G. Loosveldt. 2013. “Evaluating Relative Mode Effects in Mixed-Mode Surveys: Three Methods to Disentangle Selection and Measurement Effects,” Sociological Methods and Research 42(1): 82–104. DOI: https://doi.org/10.1177/0049124112464868.10.1177/0049124112464868
  31. Vannieuwenhuyze, J.T.A., G. Loosveldt, and G. Molenberghs. 2014. “Evaluating Mode Effects in Mixed-Mode Survey Data Using Covariate Adjustment Models,” Journal of Official Statistics 30 (1): 1–21. DOI: https://doi.org/10.2478/jos-2014-0001.10.2478/jos-2014-0001
Language: English
Page range: 981 - 1007
Submitted on: May 1, 2020
|
Accepted on: Mar 1, 2021
|
Published on: Dec 26, 2021
Published by: Sciendo
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2021 Darina N. Peycheva, Joseph W. Sakshaug, Lisa Calderwood, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.