A Donor Imputation System to Create a Census Database Fully Adjusted for Underenumeration
نویسندگان
چکیده
Following the problems with estimating underenumeration in the 1991 Census of England and Wales the aim for the 2001 Census is to create a database that is fully adjusted for net underenumeration. To achieve this, the paper investigates weighted donor imputation methodology that utilises information from both the census and census coverage survey (CCS). The US Census Bureau has considered a similar approach for their 2000 Census (see Isaki et al 1998). The proposed procedure distinguishes between individuals who are not counted by the census because their household is missed and those who are missed in counted households. Census data is linked to data from the CCS. Multinomial logistic regression is used to estimate the probabilities that households are missed by the census and the probabilities that individuals are missed in counted households. Household and individual coverage weights are constructed from the estimated probabilities and these feed into the donor imputation procedure. The first stage of the imputation procedure uses household coverage weights in conjunction with geographical information to determine the number of households that need to be imputed in the local administrative area. Donor households are selected from counted households with characteristics similar to those of the missed households. The second stage of the procedure imputes individuals missed in counted households, based on individual coverage weights. A donor is selected for each imputed individual who is then placed in a suitable counted household. Finally, certain marginal totals generated from the post-imputation database need to be calibrated to already agreed estimates at the local administrative area. To achieve this for age-sex and household size, some addition and deletion of imputed individuals is necessary.
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