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ERIC Number: EJ1189886
Record Type: Journal
Publication Date: 2017
Pages: 12
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1364-5579
EISSN: N/A
Harnessing Paradata and Multilevel Multiple Imputation When Analysing Survey Data: A Case Study
Brunton-Smith, Ian; Tarling, Roger
International Journal of Social Research Methodology, v20 n6 p709-720 2017
Missing data (attrition and non-response) are a feature of most surveys especially longitudinal/panel studies. And many such studies now have multilevel designs and hence multilevel data structures. Recent advances in imputation methodology now offer social researchers opportunities to address issues of missing data in a statistically principled way. Paradata can offer great insights in understanding the nature and causes of missingness and can be used to construct auxiliary variables to be included in imputation models. In this paper we present multilevel multiple imputation which has recently extended MI to incorporate multilevel data, making it a flexible and robust strategy for many research settings. We illustrate the procedures by analysing data drawn from a longitudinal study of prisoners. We show how paradata of that study was instrumental in guiding our approach and subsequent analysis.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: United Kingdom (England); United Kingdom (Wales)
Grant or Contract Numbers: N/A