Section 2
Nonresponse

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Response, non-response and vacancy rates
Nonresponse according to urbanization level
Nonresponse according to income strata
Adjustment for non-response

Errors due to non-response occur when some potential respondents do not provide the necessary information or the provided information proves to be unusable. Cases in which the respondent fails to answer some of the questions are referred to as partial non-response. In those cases, the missing data are imputed. Errors associated with imputation are described in section 5, which deals with processing errors. In this section, non-response includes collection non-response, which is primarily due to inability to contact the household or to refusal by household members to participate in all or part of the survey, as well as data that are collected from households but prove to be unusable.

The main impact of non-response on data quality is that it can cause a bias in the estimates if the characteristics of respondents and nonrespondents differ and the difference has an impact on the characteristics studied. Nonresponse rates are easy to calculate, but they provide only an indication of data quality, since they do not measure the bias associated with the estimates. The magnitude of non-response can be considered an indicator of the risks of bias in the estimates.

2.1 Response, non-response and vacancy rates

Since the units selected in the SHS are dwellings, interviewers must first identify ineligible dwellings, that is, dwellings occupied by persons who are not part of the target population, dwellings that no longer exist (demolished, mobile home moved or dwelling converted to business) and vacant dwellings (unoccupied, seasonal or under construction).

Then, for eligible dwellings, the proportion of households that did not respond to the survey is evaluated. This is called the collection non-response rate. Included are households that refused to participate in the survey and households for which respondents could not be contacted, either because they were absent or because of special circumstances (language problem, illness, death).

Also for eligible dwellings, the rate of unusable data is determined. Unusable data refers to the number of households whose questionnaires were at least partially completed but were rejected during data processing. When many income or expenditure questions have been left unanswered, the questionnaire is classified as incomplete and is not used.

Note that all rates provided in this section are unweighted. For the 2009 Survey of Household Spending, the final response rate is 64.5%. Table 2.1-1 shows the final response rate as well as the sample size (eligible households) broken down by refusals, units not contacted, unusable data and usable data. This information is provided for the national and provincial/territorial levels.

Table2.1-1 Sample size and response rate by province, territory and at the national level

Table 2.1-2 shows the final non-response rate; the collection non-response rate, broken down by refusals and units not contacted; and the rate of households with unusable data owing to incomplete questionnaires. The vacancy rate is also included. The rates are provided for the national and provincial/territorial levels

Note that the vacancy rates shown in the tables in section 2 include vacant dwellings (unoccupied, seasonal or under construction) and dwellings that no longer exist (demolished, mobile home moved or dwelling converted to business).

Table 2.1-2 Non-response and vacancy rates by province, territory and at the national level

2.2 Nonresponse according to urbanization level

Nonresponse varies according to urbanization level. The various national rates are shown by urbanization level in Table 2.21.

Table 2.2 Nonresponse and vacancy rates (%) by urbanization level

2.3 Nonresponse according to income strata

Since income information is unavailable for nonrespondents, it is impossible to compare income-specific non-response rates. However, the LFS sample design, used for the SHS, was constructed in such a way that in census metropolitan areas, there are strata consisting of geographic areas with a high concentration of high-income households. While the number of high-income strata remains relatively small (51 out of a total of 1,060 strata), comparison of non-response rates in this group in relation to the other strata provides relevant information on the potential effect of non-response (see Table 2.3).

Note that in addition to regular strata, the "Other" strata category includes the following four types of strata: strata with a high vacancy rate, high-cost strata, strata with a concentration of immigrants, and strata with a concentration of Aboriginals. Since the portion of the SHS sample allocated to the latter four strata was smaller, the results for them are not broken out in Table 2.3.

Table 2.3 Comparison of non-response and vacancy rates (%) in high-income strata in relation to other strata

2.4 Adjustment for non-response

To compensate for non-response, the weights in the SHS are inflated by the inverse of the weighted response rate within certain predefined groups. Following the overhaul of the LFS sample design, the non-response adjustment groups were redefined. As was the case for previous years, these groups are defined on the basis of the different urbanization levels in each province and of subprovincial geographic areas for Quebec, Ontario and British Columbia. In addition, specific non-response adjustment groups were created for high-income strata. As seen in the previous section, the number of high-income strata increased with the introduction of the new LFS sample design. As a result, it is now possible to form non-response adjustment groups for high-income strata in all provinces except Prince Edward Island. No such a group can be formed in Prince Edward Island because that province has no high-income strata.

The weighted rates differ from the rates presented in this section, since the former take the sampling weight of each household into account. An algebraic description of the adjustment for non-response is provided in Appendix A.

The adjustment of weights for non-response takes account of differences in non-response by urbanization level (as illustrated in section 2.2) and geographic area or by groups of high-income strata. It will reduce the bias insofar as the characteristics of respondents and non-respondents are similar for a given urbanization level and geographic area or for a given group of high-income strata.

It should be noted that a non-response adjustment group can be combined with another group if the number of households in the group is too small or the adjustment factor is too high.


Note

  1. Tables on non-response rates by urbanization level and province are available on request from Household Survey Methods Division.
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