A Contamination Model for Selective Editing

Di Zio Marco () and Guarnera Ugo ()
Additional contact information
Di Zio Marco: ISTAT, Italian National Institute of Statistics, Via Cesare Balbo 16, 00184 Rome, Italy.
Guarnera Ugo: ISTAT, Italian National Institute of Statistics, Via Cesare Balbo 16, 00184 Rome, Italy

Journal of Official Statistics, 2013, vol. 29, issue 4, 539-555

Abstract: The aim of selective editing is to identify observations affected by influential errors. A score function based on the impact of the potential error on target estimates is useful to prioritize observations for accurate reviewing. We assume a Gaussian model for true data and an “intermittent” error mechanism such that a proportion of data is contaminated by an additive Gaussian error. In this setting, scores can be related to the expected value of errors affecting data. Consequently, a set of units can be selected such that the expected residual error in data is below a prefixed threshold. In the context of economic surveys when positive variables are analyzed, the method is more realistically applied to logarithms of data instead of data in their original scale. The method is illustrated through an experimental study on real business survey data where contamination is simulated according to error mechanisms frequently encountered in the practical context of economic surveys.

Keywords: Statistical data editing; influential errors; finite mixture models; score function (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.2478/jos-2013-0039 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:29:y:2013:i:4:p:539-555:n:4

DOI: 10.2478/jos-2013-0039

Access Statistics for this article

Journal of Official Statistics is currently edited by Annica Isaksson and Ingegerd Jansson

More articles in Journal of Official Statistics from Sciendo
Bibliographic data for series maintained by Peter Golla ().