An alternative procedure for imputing missing data based on principal components analysis

Giovanni Di Franco ()

Quality & Quantity: International Journal of Methodology, 2014, vol. 48, issue 3, 1149-1163

Abstract: This work entailed tackling the significant problem of missing data which was solved by identifying a new substitution procedure, following an empirical approach based on the analysis of the information contained in the entire set of data collected. This procedures offers a number of advantages compared to other techniques commonly mentioned in the statistical–methodological literature. Copyright Springer Science+Business Media Dordrecht 2014

Keywords: Missing data substitution; Principal components analysis; Random missing data; Systematic missing data (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:qualqt:v:48:y:2014:i:3:p:1149-1163

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DOI: 10.1007/s11135-013-9826-4

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