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Using Paradata to Predict Nonresponse Based on EVS Data

Student: Natalia Khortseva

Supervisor: Aigul M. Klimova

Faculty: Faculty of Social Sciences

Educational Programme: Sociology (Bachelor)

Final Grade: 7

Year of Graduation: 2018

Nowadays major studies suffer from increasing nonresponse rate. High nonresponse rates lead to nonresponse bias and affect general quality of the research. Looking for solution researchers suggest two possible solutions – by applying “adaptive design” before or during the field work, or weighting final data. Both these solutions may be using paradata. Current work is aimed to assess general possibilities of paradata in predicting survey response. For achieving this goal interviewer’s contact form and interviewer’s observations collected in the 5th wave of European Value Study in Russia will be analysed. Data analysis will contain a series of binary logistic regression models which will assess general possibilities of paradata to predict nonresponse.

Full text (added May 27, 2018)

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