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A multilevel exploration of the role of interviewers in survey non-response

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This paper illustrates the use of multilevel statistical modelling of cross-classified data to explore interviewers' influence on survey non-response. The results suggest that the variability in whole household refusal and non-contact rates is due more to the influence of interviewers than to the influence of areas. The results from separate logistic regression models are compared with the results from multinomial models using a polytomous dependent variable (refusals, non-contacts and responses). Using the cross-classified multilevel approach allows us to estimate correlations between refusals and non-contacts, suggesting that interviewers who are good at reducing whole household refusals are also good at reducing whole household non-contacts.

Keywords: Interviewer effects; Interviewer variance; Multilevel models; Multinomial regression; Survey non-response

Document Type: Research Article

Affiliations: 1: University of Chicago, USA 2: London, UK

Publication date: March 1, 1999

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