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How valid can data fusion be

[working paper]

Kiesl, Hans; Rässler, Susanne

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Corporate Editor Institut für Arbeitsmarkt- und Berufsforschung der Bundesagentur für Arbeit (IAB)
Abstract "Data fusion techniques typically aim to achieve a complete data file from different sources which do not contain the same units. Traditionally, this is done on the basis of variables common to all files. It is well known that those approaches establish conditional independence of the specific variables given the common variables, although they may be conditionally dependent in reality. We discuss the objectives of data fusion in the light of their feasibility and distinguish four levels of validity that a fusion technique may achieve. For a rather general situation, we derive the feasible set of correlation matrices for the variables not jointly observed and suggest a new quality index for data fusion. Finally, we present a suitable and efficient multiple imputation procedure to make use of auxiliary information and to overcome the conditional independence assumption." (authors abstract)
Keywords correlation; data; merger; statistics; matching; data preparation
Classification Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Method basic research; development of methods
Document language English
Publication Year 2006
City Nürnberg
Page/Pages 27 p.
Series IAB Discussion Paper: Beiträge zum wissenschaftlichen Dialog aus dem Institut für Arbeitsmarkt- und Berufsforschung, 15/2006
Licence Deposit Licence - No Redistribution, No Modifications
data provider This metadata entry was indexed by the Special Subject Collection Social Sciences, USB Cologne