Modelling Measurement Errors by Object-Oriented Bayesian Networks: An Application to 2008 SHIW

Autor:	Daniela Marella, Paola Vicard
Přispěvatelé:	Mecatti, Conti, Ranalli, Marella, Daniela, Vicard, Paola
Rok vydání:	2014
Předmět:	Auxiliary variables Official statistics Observational error Object oriented bayesian networks Computer science Bayesian networks measurement error respondent error Bayesian network Household income Data mining Imputation (statistics) computer.software_genre computer
Zdroj:	Contributions to Statistics ISBN: 9783319053196
DOI:	10.1007/978-3-319-05320-2_9
Popis:	In this paper we propose to use the object-oriented Bayesian network (OOBN) architecture to model measurement errors. We then apply our model to the Italian survey on household income and wealth (SHIW) 2008. Attention is focused on errors caused by the respondents. The parameters of the error model are estimated using a validation sample. The network is used to stochastically impute micro data for households. In particular imputation is performed also using an auxiliary variable. Indices are calculated to evaluate the performance of the correction procedure and show that accounting for auxiliary information improves the results. Finally, potentialities and possible extensions of the Bayesian network approach both to the measurement error context and to official statistics problems in general are discussed.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d3e71f16ba9eb91f75319347db50a113 https://doi.org/10.1007/978-3-319-05320-2_9 Zobrazit plný text záznamu