Comparative Study of Alternatives Analysis of Incomplete Disjunctive Tables
Abstract[EN] Multiple Correspondence Analysis (MCA) studies the relationship between several categorical variables defined with respect to a certain population. However, one of the main sources of information are those surveys in which it is usual to find a certain number of absent data and conditioned questions that do not need to be answered by the whole population. In these cases, the data codification in a complete disjunctive table requires the inclusion of non-answer categories that can alter the results.
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Bibliographic InfoPaper provided by Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística) in its series BILTOKI with number 2000-08.
Date of creation: May 2000
Date of revision:
Postal: Dpto. de Econometría y Estadística, Facultad de CC. Económicas y Empresariales, Universidad del País Vasco, Avda. Lehendakari Aguirre 83, 48015 Bilbao, Spain
Find related papers by JEL classification:
- C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2000-06-05 (All new papers)
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.:
- Michael Greenacre, 2008. "Correspondence analysis of raw data," Economics Working Papers 1112, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2009.
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