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A Multilevel Exploration of the Role of Interviewers in Survey Non-Response
120
Citations
11
References
1999
Year
EngineeringParticipant ObservationSampling TechniqueMultilevel ExplorationSurvey (Human Research)ManagementConversation AnalysisPublic HealthStatisticsCross-classified Multilevel ApproachMultilevel Statistical ModellingComplex SamplePopulation HouseholdMultilevel ModelingCross-sectional StudySociologySurvey Non-responseWeb Survey MethodQuantitative Social Science ResearchDemographyWhole Household RefusalSurvey Methodology
Summary 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.
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