1. Canadian Census E&I – Lessons Learned from 2006 with Plans for 2011
Mike Bankier, Statistics Canada,
Work Session on Statistical Data Editing
Vienna Austria, April

2. Outline of Talk Changes Made for 2006 Census
Impact of adjusting occupancy status and imputation of total non-response households
Processing of demographic variables with an emphasis on age
Possible enhancements to E&I for 2011

3. Changes to 2006 Census 73% of dwellings mailed questionnaires
18% of dwellings responded by Internet
85% gave permission to link to tax form
Questionnaires captured using ICR
Non-Response Follow-Up (NRFU) done from centralized offices
Failed Edit Follow-Up (FEFU) done from call centres

4. 2006 Census Changes
These new approaches reduced the field staff required by 46%
Because of widespread labour shortages in some regions, the collection period was extended from mid-July to the end of Aug. (Census day May15)
National NR rate 2.8% in 2006 vs 1.6% in 2001

5. Dwelling Classification Survey
Mistakes made in field classifying dwellings as occupied or unoccupied.
Sample of dwellings revisited to reassess occupancy status for dwellings where no response received
DCS estimated
17.4% of 934,564 dwelling classified as unoccupied were occupied and
29.1% of 366,527 dwellings classified as occupied but with no responses were actually unoccupied
Occupancy status for individual dwellings adjusted. Resulted in a 3.6% increase in the number of occupied dwellings and a 5.2% decrease in the number of unoccupied dwellings

6. Imputation of Total NR Households
After the DCS adjustment, total non-response dwellings had all responses imputed by borrowing unimputed responses from another household
Using a single donor for total non-response was less likely to produce implausible results
Weighting used in 2001 to convert unoccupied dwellings to occupied - it could transfer population from one city block to another and be noticed by users

7. Demographic E&I
Demographic E&I does minimum change imputation for blanks and inconsistencies so later program can form Census families
All demographic variables for all persons in household are imputed simultaneously using CANCEIS
Three types of Census families
Couples without children
Couples with children
Lone Parents with children

8. Couple Editing Concepts
For a couple, they should be
both adults (age >=15) and
both married or both common-law and
have appropriate relationships to Person 1

9. Child/Parent Editing Concepts
For a child/parent pair
At least one parent must be 15 or more years older than the child and
A female parent must not be more than 50 years older than a child and
The relationships to Person 1 should be appropriate

10. 0.85% In Wrong 5 Year Age Range - Data Capture Error

11. Analysis of Imputation of Age
AGEU and AGE represent respectively the age of the person before and after minimum change donor imputation
99.11% had AGEU = AGE
0.61% had AGEU = Blank/Invalid
0.28% had AGEU ≠ AGE because of an inconsistency between AGEU and another variable

12. AGE Imputation for WIFE

13. Female Lone Parent vs Child Ages Before Imputation

14. Female Lone Parent vs Child Ages After Imputation

15. WIFE vs Child Ages Before Imputation

16. WIFE vs Child Ages After Imputation

17. Number of Children by Age Difference With Mother

18. 2011 Changes – Small Domains
Small domain (e.g. centenarians, same sex married couples) can have upwards bias because of response or data capture errors for persons outside the small domain
Sometimes no alternate source of data to verify the small domain count and the domain is too large to be manually reviewed 100%

19. 2011 Changes – Small Domains
Manually review 20% sample of persons age 95+ to determine those with incorrect age
For other 80% of persons age 95+, use nearest neighbour imputation to determine those with incorrect age
Then in 2nd step, blank out incorrect ages and impute

20. 2011 Changes – Use Failed Records as Donors
Sometimes stratum failure rate is so high that number of donors is insufficient
Failed records could be used as donors since frequently failed record is missing just one or two responses and would be suitable for imputing other responses

21. 2011 Changes - More Minimum Change Donor Imputation
Will do more minimum change donor imputation and less deterministic imputation where possible
Will combine modules so more variables are imputed simultaneously where possible

22. Concluding Remarks
Sophisticated E&I programs can do a better job detecting and resolving edit failures
With this comes the responsibility to make few assumptions regarding the characteristics of the non-respondents or those giving inconsistent responses
The impact of imputation should be made clear to users
E&I should not be viewed as a panacea such that data quality standards can be lowered