ADDITIONAL EDITING
A range of processes were applied to the diary information to check that specific conditions were correctly coded according to the coding rules; that errors had not occurred in coding; and that relationships between household and diary information were consistent. A Query Resolution System was also used to ensure that:
- an accurate record of decisions was kept;
- coding of episodes was consistent;
- the Activity Classification was updated for unusual or unknown situations; and
- coders could continue to process diaries if they could not resolve an issue within a short time.
A range of edits was also applied to the household, individual and diary information to double check that logical sequences had been followed in the questionnaires; that specific values lay within expected ranges; and that relationships between items were consistent. Unusually high values for the continuous variables such as income, the number of hours worked and duration of activities were investigated to determine whether there had been errors in entering the data.
Imputation for missing values
Some households did not supply all the required information but supplied sufficient information to be retained in the sample. Where there was income data missing from the questionnaire this could be imputed in some cases. For the Time Use Survey missing income data was imputed in two ways. Firstly, missing data for income relating to government pensions and allowances was clerically imputed by looking at the other household information and using the guidelines from Centrelink and Department of Veterans Affairs to determine the missing value. Secondly, missing data for wages and salary income was imputed by replacing each missing value with a value reported by another person (referred to as a donor).
Donor records were selected by finding fully responding persons with information on various characteristics, such as state, sex, age, labour force status and income, that matched the person with missing information. As far as possible, the imputed information is an appropriate proxy for the information that is missing. Donors were randomly chosen from the pool of individual records with complete information for the questions where the missing information occurred.
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