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Towards a Fully Adjusted Census Database for the 2011 Census Christine Sexton (ONS)

Towards a Fully Adjusted Census Database for the 2011 Census Christine Sexton (ONS) Alan Taylor (ONS) James Brown (ADMIN @ IoE). Outline. Overview of the Census Coverage Assessment and Adjustment Strategy for 2011 The 2001 Adjustment Strategy Learning from 2001

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Towards a Fully Adjusted Census Database for the 2011 Census Christine Sexton (ONS)

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  1. Towards a Fully Adjusted Census Database for the 2011Census Christine Sexton (ONS) Alan Taylor (ONS) James Brown (ADMIN @ IoE)

  2. Outline • Overview of the Census Coverage Assessment and Adjustment Strategy for 2011 • The 2001 Adjustment Strategy • Learning from 2001 • Assessment of the 2001 Adjustment System • The Way Forward

  3. Census Coverage Survey 2011 Census Matching Quality Assurance Estimation Adjustment Overview of the Coverage Assessment and Adjustment Process

  4. The 2001 Adjustment Strategy • Stage 1: Imputation of missed households (with people) • Model to derive predicted census household coverage probabilities using matched census to CCS data to obtain coverage weights • tenure, ethnicity, household structure • Calibrate coverage weights to key variable estimates • tenure exactly • Impute households with people into the database • whole household records copied

  5. The 2001 Adjustment Strategy • Stage 2: Imputation of missed individuals into counted households • Model to derive predicted person within counted census household coverage probabilities using matched census to CCS data • age, sex, activity, household structure, LA • Calibrate coverage weights to key variable estimates at local authority level • age-sex groups exactly • Impute people into census counted households • whole person records copied

  6. The 2001 Adjustment Strategy • Stage 3: Final adjustment • Further adjustments to meet local authority level estimates for age-sex groups and household size distributions • taking out imputed individuals • putting in extra individuals (pruning and grafting) Ref: Steele, Brown and Chambers (2001), JRSS, series A.

  7. Learning From 2001 • Insufficient control of household size and characteristics for imputed households • Too many people in certain age-sex groups added at household imputation stage • Much time spent “pruning and grafting” • Insufficient heterogeneity in the imputed population for some characteristics • Whole records copied to imputed households and individuals • Ensured Census edit rules satisfied but may not reflect variability in population

  8. Assessing the Performance of the 2001 System • Used simulations • Uses 2001 census extracts as the ‘true population’ • modelled 2001 matched census and CCS data • 10 simulated censuses and CCSs for one Estimation Area (two LAs) • Census coverage 94% • 200,000 households • 490,000 persons • Used true totals as calibration constraints LA age-sex group totals, activity, tenure, household size

  9. Performance measures

  10. Relative Average Bias Results for Tenure

  11. RRAMSE Results for Tenure

  12. Relative Average Bias Results for Males by Age

  13. RRAMSE Results for Males by Age

  14. Relative Average Bias Results for Activity

  15. RRAMSE Results for Activity

  16. The Way Forward • Aim to improve imputation by gaining better control of numbers of individuals imputed into households and their characteristics • Correct distribution of age group and household size at lower levels of geography • Reduce time spent on final adjustment (pruning and grafting)

  17. Modelling Missed Individuals • In 2001 we modelled individuals missed within counted households • no direct control of individuals missed within missed households • Proposed new model – all missed individuals in single model • missed within counted households • missed within missed households • Calibrate coverage weights for all individuals then split weights into two components based on the model

  18. Reverse the order of imputation • In 2001 household imputation carried out first • Within household imputation used to make up shortfall • Household weights did not match individual totals • Imputed households did not contain correct types of individuals

  19. Reverse the order of imputation • New person model gives direct control over split between two sources of undercount • Can put missed individuals into counted households first to complete counted households • Then model census household coverage • Calibrate household weights to key variables at EA level – tenure and household size • Also calibrate household weights to key individual level variables from the persons in missed HHs totals – age-sex groups – at LA level to recover totals at the individual level

  20. Conclusions • By implementing the proposed changes we aim to improve on the 2001 system by gaining better control of the age-sex by household size distribution of the adjusted database and reduce the need for the final stage adjustment • Analysis of 2001 method gives us a bench-mark to compare changes • Work in progress

  21. Questions? Christine.sexton@ons.gov.uk

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