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The importance of data quality

Checking the accuracy of vital events records

Methods and tools to evaluate the quality of vital statistics

Tabulation and generation of vital statistics for national policy

Presentation, communication and dissemination of vital statistics

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Methods and tools to evaluate the quality of vital statistics

Imputation of missing values

Sometimes it is necessary to impute values for missing data, to generate more complete statistics. Many statistical offices are familiar with imputation methods, which also can be used on vital events records when fields such as province or place of residence, sex, age and date of birth of the decedent are missing. Each variable has to be imputed based on some other information – for example, if the data are missing for usual residence, the province of occurrence of event can be used. Missing data on sex can be imputed based on COD information and a logistic regression. Missing age values can be imputed based on the date of birth years (if provided) or by imputing the age value to the median age observed for groups of similar causes of death. In general, these imputations affect few records each year.


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