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Use of cluster analysis for collapsing imputation classes / E. R. Langlet.: CS11-613/89-19E-PDF

"The problem of collapsing the imputation classes defined by a large number of cross-classifications of auxiliary variables is considered. A solution based on cluster analysis to reduce the number of levels of auxiliary variables to a reasonably small number of imputation classes is proposed. The motivation and solution of this general problem are illustrated by the imputation of age in the Hospital Morbidity System where auxiliary variables are sex and diagnosis"--Abstract.

Permanent link to this Catalogue record:
publications.gc.ca/pub?id=9.837472&sl=0

Publication information
Department/Agency
  • Canada. Statistics Canada. Social Survey Methods Division.
TitleUse of cluster analysis for collapsing imputation classes / E. R. Langlet.
Series title
  • Working paper ; 89-19
Publication typeMonograph - View Master Record
Language[English]
FormatDigital text
Electronic document
Note(s)
  • Digitized edition from print [produced by Statistics Canada].
  • "Working paper no. SSMD-89-019 E."
  • Includes bibliographic references.
  • Prefatory material in English and French.
Publishing information
  • [Ottawa] : Statistics Canada, 1989.
Author / Contributor
  • Langlet, E. R.
Description14 p.
Catalogue number
  • CS11-613/89-19E-PDF
Departmental catalogue number11-613E
Subject terms
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