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:
http://publications.gc.ca/pub?id=9.837472&sl=0

Publication information
Department/Agency Canada. Statistics Canada.Social Survey Methods Division.
Title Use of cluster analysis for collapsing imputation classes / E. R. Langlet.
Series title Working paper ; 89-19
Publication type Series - View Master Record
Language [English]
Format Electronic
Electronic document

Archived Content

Archived information is provided for reference, research or recordkeeping purposes. It is not subject to the Government of Canada Web Standards and has not been altered or updated since it was archived. Please contact the authoring department to request a format other than those available.


Note: The URLs contained in this/these document(s) may no longer be functional
Having trouble opening this 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.
Description 14 p.
Catalogue number
  • CS11-613/89-19E-PDF
Departmental catalogue number 11-613E
Subject terms Statistical analysis

Date modified: