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Published byAlbert Watts Modified over 9 years ago
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Measuring Interviewer Effects on Survey Error in SHARE Annelies Blom Julie Korbmacher Ulrich Krieger
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Motivation Korbmacher and Schröder (2010): consent to record linkage (SHARE wave 3) „The decision making process is mainly influenced by the interview situation which in turn is driven by the interviewer-respondent-interaction ”
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The role of the interviewer …make contact …gain cooperation …ask survey questions …conduct measurements …record answers and measurements …maintain respondents’ motivation throughout the interview Standardized interviews to reduce variation in the entire data collection process
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Types of interviewer effects in surveys Interviewer Measurement Unit nonresponse ContactCooperation Item nonresponse Nonresponse- Error Measurement- Error
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Survey of Health, Ageing and Retirement in Europe (SHARE) Multidisciplinary Micro data on health, socio-economic status, social and family networks bi-annual, longitudinal (wave 1 in 2004) 20 European countries SHARE-DE (Wave 4) specials: Record linkage (Pilot in wave 3) Collecting biomarkers Nonresponse experiment
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Interviewer effects examined in SHARE Germany Wave 4 Interviewer Income item nonresponse Consent to biomarkers blood pressure height waist circumference dried blood spots Unit nonresponse (incentives) No unconditional incentive 10€ unconditional incentive 20€ unconditional incentive 40€ unconditional incentive Consent to record linkage
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Measuring and Explaining interviewer effects Step 1: Measuring interviewer effects Step 2: Explaining interviewer effects Who are the SHARE interviewers? Interviewer questionnaire Underlying assumptions: Interviewers differentially impact on the data collection process This differential impact is related to their – conscious and subconscious – appearance and actions These actions can be explained by characteristics collected in an interviewer survey
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Interviewer survey 2011 Interviewer Training Wave 4 (trained 197 interviewers) Paper-and-pencil Voluntary and no incentives At the end of the training session Response rate: 83% Link via InterviewerID to SHARE Survey data!
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Conceptual framework 4 dimensions of interviewer characteristics Unit non- response Unit non- response (incentives) Consent to biomarker collection Consent to record linkage Item nonresponse (income) General attitudes Own behavior Experience with measurements Expectations 5 aspects of SHARE Wave 4 (Germany)
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Conceptual framework General interviewer attitudes Reasons for being an interviewer Attitudes towards best practice Trust and data protection concerns Interviewers‘ own behavior Interviewer as respondents Membership in social networks Income Blood donation Hypothetical questions: disclose sensitive information consent to record linkage consent to biomarkers
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Conceptual framework Interviewers’ experience with measurements Conducting standardized interviews SHARE Conducting blood sugar tests Interviewers’ expectations of unit response, consent and item response rates Expected response and consent rates: Different incentive groups Biomarker measurements Record linkage Income
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Some results of the interviewer survey Nonresponse Interviewers were confident that the higher the value of the incentive the more successful they would be in recruiting respondents. Interested in learning about the lives of other people Important to work on research that is relevant to society expect higher RRs expect lower RRs Using of social networks (facebook)
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Some results of the interviewer survey Consent to record linkage Expected consent rate: 59,2% Interviewers who would reveal personal information expect a significantly higher consent rate. SSN Telephone number Private Address Address of health insurer
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Some results of the interviewer survey Interviewers who would consent to data linkage expect a significantly higher consent rate. Credit history Employment history Medical records Social benefits Interviewer who are part of social networks expect significantly lower record linkage rates.
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Outlook Next steps: Completion of the survey Linking with SHARE survey data to learn more about interviewer effects Can we explain interviewer effects in SHARE with the interviewers’ characteristics allocated in the interviewer survey?
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