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Article
Transfer of variables between different data-sets, or Taking ‘previous research’ seriously
BMS: Bulletin of Sociological Methodology (2012)
  • Bojan Todosijević
Abstract
Given two methodologically similar surveys, a question not asked in one survey could be
seen as a special case of the missing data problem. Hence, the transfer of data across data
sets (‘‘statistical matching’’ or ‘‘data fusion’’) could be achieved applying the procedures
for Bayesian multiple imputation of missing values. To tackle the problem of conditional
independence, which this approach creates, a simulated data set could serve as the
‘‘third data set’’ that conveys information about the relationship between variables
not commonly observed. This paper presents a model for transferring data between
different data sets based on multiple imputation (MI) approach. The results show that
statistical matching based on MI principles can be a useful research tool. The entire
enterprise is interpreted in the sense of taking the ‘‘previous research’’ into account
seriously.
Publication Date
2012
DOI
10.1177/0759106311426992
Citation Information
Bojan Todosijević. "Transfer of variables between different data-sets, or Taking ‘previous research’ seriously" BMS: Bulletin of Sociological Methodology Vol. 113 Iss. 1 (2012) p. 20 - 39
Available at: http://works.bepress.com/bojan_todosijevic/12/