Interviewers' and Respondents' Joint Production of Response Quality in Openended Questions: A Multilevel Negativebinomial Regression Approach
Abstract: Open-ended questions are an important methodological tool for social science researchers, but they suffer from large variations in response quality. In this contribution, we discuss the state of research and develop a systematic approach to the mechanisms of quality generation in open-ended questions, examining the effects from respondents and interviewers as well as those arising from their interactions. Using data from an open-ended question on associations with foreigners living in Germany from the ALLBUS 2016, we first apply a two-level negative binomial regression to model influences on response quality on the interviewer and respondent level and their interaction. In a second regression analysis, we assess how qualitative variation (information entropy) in responses on the interviewer level is related to interviewer characteristics and data quality. We find that respondents' education, age, gender, motivation and topic interest influence response quality. The interviewer-rela
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
Interviewers' and Respondents' Joint Production of Response Quality in Openended Questions: A Multilevel Negativebinomial Regression Approach ; volume:15 ; number:1 ; year:2021 ; pages:43-76
Veröffentlichungsversion
begutachtet (peer reviewed)
Methods, data, analyses ; 15, Heft 1 (2021), 43-76
- Klassifikation
-
Sozialwissenschaften, Soziologie, Anthropologie
- Ereignis
-
Veröffentlichung
- (wo)
-
Mannheim
- (wer)
-
SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
- (wann)
-
2021
- Urheber
-
Barth, Alice
Schmitz, Andreas
- DOI
-
10.12758/mda.2020.08
- URN
-
urn:nbn:de:101:1-2022062717043896571711
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:33 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Barth, Alice
- Schmitz, Andreas
- SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
Entstanden
- 2021