Measurement Error Calibration in Mixed-mode Sample Surveys

Mixed-mode surveys are known to be susceptible to mode-dependent selection and measurement effects, collectively referred to as mode effects. The use of different data collection modes within the same survey may reduce selectivity of the overall response but is characterized by measurement errors di...

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Bibliographic Details
Published in:Sociological methods & research 2015-08, Vol.44 (3), p.391-426
Main Authors: Buelens, Bart, van den Brakel, Jan A.
Format: Article
Language:English
Subjects:
Calibration
Crime
Data Collection
Error of Measurement
Estimating techniques
Foreign Countries
Inferences
Measurement errors
Regression (Statistics)
Responses
Risk
Simulation
Surveys
Victims
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Summary:Mixed-mode surveys are known to be susceptible to mode-dependent selection and measurement effects, collectively referred to as mode effects. The use of different data collection modes within the same survey may reduce selectivity of the overall response but is characterized by measurement errors differing across modes. Inference in sample surveys generally proceeds by correcting for selectivity—for example, by applying calibration estimators—and ignoring measurement error. When a survey is conducted repeatedly, such inferences are valid only if the measurement error remains constant between surveys. In sequential mixed-mode surveys, it is likely that the mode composition of the overall response differs between subsequent editions of the survey, leading to variations in the total measurement error and invalidating classical inferences. An approach to inference in these circumstances, which is based on calibrating the mode composition of the respondents toward fixed levels, is proposed. Assumptions and risks are discussed and explored in a simulation and applied to the Dutch crime victimization survey.
ISSN:0049-1241
1552-8294
DOI:10.1177/0049124114532444