Canadian Census E&I – Lessons Learned from 2006 with Plans for 2011 Mike Bankier, Statistics Canada, bankier@statcan.ca Work Session on Statistical Data Editing Vienna Austria, April 21-23 2008

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

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

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

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

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

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

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

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

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

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

AGE Imputation for WIFE

Female Lone Parent vs Child Ages Before Imputation

Female Lone Parent vs Child Ages After Imputation

WIFE vs Child Ages Before Imputation

WIFE vs Child Ages After Imputation

Number of Children by Age Difference With Mother

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%

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

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

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

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