Canadian census e i lessons learned from 2006 with plans for 2011
This presentation is the property of its rightful owner.
Sponsored Links
1 / 22

Canadian Census E&I – Lessons Learned from 2006 with Plans for 2011 PowerPoint PPT Presentation


  • 50 Views
  • Uploaded on
  • Presentation posted in: General

Canadian Census E&I – Lessons Learned from 2006 with Plans for 2011. Work Session on Statistical Data Editing Vienna Austria, April 21-23 2008. Mike Bankier, Statistics Canada, [email protected] Outline of Talk. Changes Made for 2006 Census

Download Presentation

Canadian Census E&I – Lessons Learned from 2006 with Plans for 2011

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Canadian census e i lessons learned from 2006 with plans for 2011

Canadian Census E&I – Lessons Learned from 2006 with Plans for 2011

Work Session on Statistical Data Editing

Vienna Austria, April 21-23 2008

Mike Bankier, Statistics Canada, [email protected]


Outline of talk

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

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

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

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

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

  • 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

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

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

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


Analysis of imputation of age

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

AGE Imputation for WIFE


Female lone parent vs child ages before imputation

Female Lone Parent vs Child Ages Before Imputation


Female lone parent vs child ages after imputation

Female Lone Parent vs Child Ages After Imputation


Wife vs child ages before imputation

WIFE vs Child Ages Before Imputation


Wife vs child ages after imputation

WIFE vs Child Ages After Imputation


Number of children by age difference with mother

Number of Children by Age Difference With Mother


2011 changes small domains

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 domains1

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

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

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

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


  • Login