CANCEIS (CANadian Census Edit and Imputation System)
The contents related to CANCEIS are shown in the following sections:
CANCEIS is an edit and imputation system developed by Statistics Canada. It was designed based upon the Nearest-neighbour Imputation Methodology (NIM) and was first used to perform edit and imputation on census data. CANCEIS performs minimum change nearest-neighbour imputation and deterministic imputation. The NIM allows the simultaneous hot-deck imputation of numeric and categorical variables based on a single donor. The NIM identifies donors for the entire household, not only for the individuals. For each failed household, the NIM identifies a set of potential donors (nearest neighbours) which are as similar as possible to the failed household to be imputed. For each nearest neighbour, the smallest subsets of variables which, if imputed, allow the imputed record to pass the edits, are identified. One of those imputation actions is randomly selected by giving a better chance to those imputation actions that are simultaneously closer to the failed household and the potential donor.
Status: validated
Author: Statistics Canada
GSBPM code:
5.3 Review and validate
5.4 Edit and impute
Keywords: editing, nearest-neighbour donor imputation, numeric and categorical variables
To get the CANCEIS software as well as the methodological and technical documentation, please contact Statistics Canada.
OTHER DOCUMENTATION
Bruzzone, S., A. Manzari, M. Pappagallo, e A. 2007. “Indagine sulle Cause di Morte: Nuova procedura automatica per il controllo e la correzione delle variabili demo-sociali“. Documenti, N. 6. Roma: Istat.
Manzari, A., and A. Reale. 2001. “Towards a new system for edit and imputation of the 2001 Italian Population Census data: A comparison with the Canadian Nearest-neighbour Imputation Methodology“. In ISI World Statistics Congress Proceedings 53rd Session, International Statistical Institute, Seoul, 2001.