Relationship Between the Level of Non-Responses in Personal Interviews and the Type of Housing of the Respondent (on the Example of Analysis of Paradata ESS)

Authors

DOI:

https://doi.org/10.29038/2306-3971-2020-02-30-40

Keywords:

paradata, ESS, metadata

Abstract

Collection and analysis of respondents in mass surveys can improve the quality of information obtained, in particular by reducing the level of non-response. The study of paradata allows us to find out how those who refuse to participate in the study differ from the participants that agreed. This allows researchers to improve the interviewer's guide and develop an individual approach to each respondent. The importance of measuring the respondent's life circumstances according to the results of the ESS study was revealed, including the influence of the respondent's real estate characteristics on the probability of participating in the interview. On the example of ESS, the methodological documents of the research and the array of counselors were analyzed in order to investigate how characteristics of apartment affect the level of non-response in the ESS study.

The analysis was based on paradata and a guide for the ESS 2010 (ESS-5) and 2018 (ESS-9) interviewers in Germany. It was found that the methodological and accompanying documents of the German ESS have undergone changes that should solve the research problems and should help the interviewer to determine correctly the characteristics of the respondent's home and the respondent's commitment to the interviewer. The interview plan and the interviewer's instructions include all the respondent's answers and follow-up, they still do not have written instructions for the respondents depending on the type of house in which he lives. The importance of parada has been emphasized in previous ESS studies, but despite this, the influence of paradata on the level of non-response is not raised and is not taken into account in the ESS study of almost all countries.

To analyze the impact of the respondent's real estate characteristics on the probability of non-response to the questionnaire, a binary logistic regression was constructed. It was found that the variables "house type" and "house condition". only partially explain the possibility of establishing contact with a potential respondent.

References

Conrad, F., Tourangeau, R., Couper, M., Zhang, C. (2017). Reducing speeding in web surveys by providing immediate feedback. Survey Research Methods, 11(1), 45–61. https://doi.org/10.18148/srm/2017.v11i1.6304

Couper, M. P. (1998). A Measuring Survey Quality in a CASIC Environment. Invited paper presented at the Joint Statistical Meetings of the American Statistical Association. Proceedings of the Survey Research Methods Section, ASA, Achieving Quality in Surveys, Dallas, pp. 41–49.

Couper, M. P., Trotman, M. (2007). Whither the Web: Web 2.0 and the Changing World of Web Surveys. The Challenges of a Changing World: Proceedings of the Fifth International Conference of the Association for Survey Computing. Berkeley, UK, pp. 7–16.

European Social Survey (ESS), Response Based Quality Assessment (2020). Retrieved April 02, 2020 from https://www.europeansocialsurvey.org/

Fowler, F. (2010). Design and evaluation of questionnaires. Chongqing: Chongqing University Press.

Groves, R., Wagner, J., Peytcheva, E. (2007). Use of interviewer judgments about attributes of selected respondents in post-survey adjustment for unit nonresponse: An illustration with the National Survey of Family Growth. In: Proceedings of the Section on Survey Research Methods of the American Statistical Association, pp. 3428–3431. Retrieved April 07, 2020 from http://www.asasrms.org/Proceedings/y2007/Files/JSM2007-000782.pdf

Jill, Z. (2011). What Day of the Week Should You Send Your Survey? SurveyMonkey Blog. Retrieved April 07, 2020 from https://www.surveymonkey.com/curiosity/day-of-the-week/

Kovalska, Y. (2019). The adaptation of Warners Index of Status Characteristics (ISC): An empirical study in Kyiv. Sociology: Theory, Methods, Marketing, 3, 124–142. https://doi.org/10.15407/sociology2019.03.124

Kreuter, F., Casas-Cordero, C. (2010). RatSWD, working paper, No 136, p.16. Retrived April 05, 2020 from http://www.ratswd.de/download/RatSWD_WP_2010/RatSWD_WP_136.pdf

Lessler, T., Kalsbeek, W. D. (1992). Nonsampling error in surveys. New York: Wiley-Interscience.

O’Reilly, J. (2009). Paradata and Blaise: A review of recent applications and research. Paper presented at the 12th International Blaise Users Conference (IBUC). Latvia, pp. 1–5. Retrieved April 03, 2020 from http://www.blaiseusers.org/2009/papers/7d.pdf

Sydorov, M. (2011). Using of paradata in social researches. Sociology: Theory, Methods, Marketing, 4, 198–208.

Sydorov, M., Bilous, Ye. (2013). Approaches to the Аnalysis of Data with Nonresponse. Sociological Studios, No 2(3), 64–69. Retrieved April 06, 2020 from https://sociostudios.eenu.edu.ua/index.php/socio/article/view/82/59

Sydorov, M., Khodakivska, Yu. (2014). Using paradata for regulating the level of non-response (with ESS data). Bulletin of Taras Shevchenko National University of Kyiv. Sociology, 1, 62–68. Retrieved April 07, 2020 from http://nbuv.gov.ua/UJRN/VKNU_soc_2014_1_13

Published

24.12.2020

Issue

Section

METHODOLOGY AND METHODS OF SOCIOLOGICAL RESEARCH