Use of cluster analysis for collapsing imputation classes: 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.
|Department/Agency||Statistics Canada. Social Survey Methods Division.|
|Title||Use of cluster analysis for collapsing imputation classes|
|Series Title||Working paper ;|
|Publication Type||Series - View Master Record|
|Electronic Document|| |
Information identified as archived 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.
We invite you to consult the Frequently Asked Questions page for additional information regarding the Archived Content notice.
Note: The URLs contained in this/these document(s) may no longer be functional
|Note||Digitized edition from print [produced by Statistics Canada]. "Working paper no. SSMD-89-019 E."|
|Number of Pages||14 p.|
|Departmental Catalogue Number||11-613E|
|Subject Terms||Statistical analysis|
- Date modified: