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-related variance in response length is 36%. Whereas interviewer characteristics (age, gender, education, experience) do not have a direct effect, they impact on response quality due to interactions between interviewer and respondent characteristics. Notably, an interviewer's experience has a positive effect on response quality only in interaction with highly educated respondents.