Statistical Data Editing

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Author(s): Claudio Conversano (University of Cagliari, Italy)and Roberta Siciliano (University of Naples, Federico II, Italy)
Copyright: 2009
Pages: 6
Source title: Encyclopedia of Data Warehousing and Mining, Second Edition
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-60566-010-3.ch280

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Abstract

Statistical Data Editing (SDE) is the process of checking and correcting data for errors. Winkler (1999) defines it the set of methods used to edit (clean-up) and impute (fill-in) missing or contradictory data. The result of SDE is data that can be used for analytic purposes. Editing literature goes back to 60’s with the contributions of Nordbotten (1965), Pritzker et al. (1965) and Freund and Hartley (1967). A first mathematical formalization of the editing process is in Naus et al. (1972), who introduce a probabilistic criterion for the identification of records (or the part of them) that failed the editing process. A solid methodology for generalized editing and imputation systems is developed in Fellegi and Holt (1976). The great break in rationalizing the process came as a direct consequence of the PC evolution in the 80’s: Editing started to be performed on-line on PCs even during the interview and by the respondent in computer assisted self-interviewing (CASI) models of data collection (Bethlehem et al., 1989). Nowadays, SDE is a research topic in academia and statistical agencies. The European Economic Commission periodically organizes a workshop on the subject concerning both scientific and managerial aspects of SDE (www.unece.org/stats).

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