Missing data in optimal scaling
AbstractWe propose a procedure to assess a measure for a latent phenomenon, starting from the observation of a wide set of ordinal variables affected by structured missing data. The proposal is based on Nonlinear PCA technique to be jointly used with an ad hoc imputation method for the treatment of missing data. The procedure is particularly suitable when dealing with ordinal, or mixed, variables, which are strongly interrelated and in the presence of specific patterns of missing observations
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Bibliographic InfoPaper provided by Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano in its series Departmental Working Papers with number 2005-19.
Date of creation: 01 Jan 2005
Date of revision:
Nonlinear PCA; monotone missing data; ordinal variables; missing data passive;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-01-01 (All new papers)
- NEP-ECM-2006-01-01 (Econometrics)
- NEP-MKT-2006-01-01 (Marketing)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Pieralda Ferrari & Paola Annoni & Sergio Urbisci, 2005. "A Proposal for Setting-up Indicators in the Presence of Missing Data: the Case of Vulnerability Indicators," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1002, Universitá degli Studi di Milano.
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