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Keywords:

  • Cross-classified models;
  • Interviewer observations;
  • Los Angeles Family and Neighborhood Survey;
  • Measurement error;
  • Paradata

Summary.  Interviewer observations made during the process of data collection are currently used to inform responsive design decisions, to expand the set of covariates for non-response adjustments, to explain participation in surveys and to assess non-response bias. However, little effort has been made to assess the quality of such interviewer observations. Using data from the Los Angeles Family and Neighborhood Survey, the paper examines measurement error properties of interviewer observations of neighbourhood characteristics. Block level and interviewer covariates are used in multilevel models to explain interviewer variation in the observations of neighbourhood features.