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Scope and purpose
Concepts are the subjects of inquiry and analysis that are of interest
to users. They refer to general characteristics or attributes of a statistical
unit or of a population of like statistical units. Variables are
the indicators used to measure the concepts. It is important that the definitions
of the concepts and of the specific variables required for the measurement
of the concepts be unambiguous and clearly specified in the context of the
analytical purposes for which the data are to be collected. Since all categorical
statistical data need to be classified for analysis, the classification
criteria chosen to group data systematically need to be suitable for these
analytical purposes.
Principles
In order to draw conclusions from a set of data, it is extremely important
for users to have input to and knowledge of the concepts underlying the
data, i.e., what the data purport to measure. Although the use of harmonized
definitions of concepts, variables and classifications will assist users
in comparing and integrating data, such definitions may need to be modified
to meet the intended uses of the data. The definitions of the concepts,
variables and classifications should be carefully documented, and any
differences from standards or from those used to produce related data
should be noted. This documentation is especially important for users
who wish to apply the data for other than their intended use.
Sometimes, there is more than one way to measure a concept. The variables
and classifications chosen to measure a concept will also need to take
into account factors such as the ease of obtaining the information required,
the respondent burden imposed, the collection method, the context in which
the question(s) must be asked, the processing of the data (especially
editing, imputation and weighting techniques), whether the information
can be obtained from administrative records, and the costs associated
with collection and processing. Thus, the measurement approach adopted
may be more or less successful in providing the desired interpretation
of the concept. A variable chosen at one point in time may become obsolete
later if new factors come into play and may therefore need to be modified
or changed.
Guidelines
- Specify concepts and variables clearly and relate them to their intended
use. Wherever possible, make use of the standard definitions of concepts,
variables, classifications, statistical units and populations established
under the Statistics Canada Policy
on Standards (Statistics Canada, 1998c). In choosing naming conventions,
take into account the similarity or dissimilarity with existing standards
and usage. Use titles from existing standards only for what is defined
in the standards.
- To maximize flexibility of use, code microdata and maintain files
at the lowest possible level of the appropriate classification. Aggregation
at a higher level may be required for particular analytical purposes
or to satisfy confidentiality or data reliability constraints. Wherever
possible, use a common collapsing strategy for these aggregations and
define them in terms of the classes or higher level aggregations of
the standard. Document differences. Use classifications that reflect
both the most detailed and the collapsed levels. Make clear to users
how these fit into higher-level (i.e., less detailed) classifications.
- Use standard definitions to make it possible to compare data collected
from different sources and to integrate data across sources (Statistics
Canada, 1998b). Statistics Canada has standard classifications of industries,
products, occupations and geography (Statistics Canada, 2001b, 2001c,
2002b, 2003c) as well as of a large number of other variables used for
social and economic statistics (Statistics Canada, 2000c).
- In addition to Statistics Canada’s standard classifications,
there are international standard classifications produced by the United
Nations Statistical Office, the International Labour Office, Eurostat,
and other international and regional agencies. The Standards Division
has produced official concordances to a number of international standard
classifications. When there is a requirement to provide data to international
agencies, use official concordances when they are available.
- Use standard units of observation to facilitate the comparison of
data. Classifications are usually designed with particular units of
observation in mind. For example, the North American Industry Classification
is designed primarily for classifying establishments.
- Be aware of derived statistical activities or statistical frameworks
(e.g., the System of National Accounts) whose definitions of concepts
and variables may have a significant effect on specific data collection
activities (Statistics Canada, 1989).
- In the absence of an official standard, examine the concepts, variables
and classifications being used by related statistical programs and consult
with the Standards Division when necessary.
References
Statistics Canada (1989). A User Guide to the Canadian System
of National Accounts. Statistics Canada Catalogue no. 13-589.
Statistics Canada (1998b). Policy
on Standards. Policy Manual, 2.10.
Statistics Canada (2000c). Integrated Metadatabase: http://stdsweb/standards/imdb/imdb-menu.htm
(STC intranet site).
Statistics Canada (2001b). National Occupational Classification
for Statistics, 2001. Statistics Canada Catalogue no. 12-583-XPE.
Statistics Canada (2001c). Standard Classification of Goods 2001
(based on the Harmonized Commodity Description and Coding System). Statistics
Canada Catalogue no. 12-580.
Statistics Canada (2002b). Standard Geographical Classification,
SGC 2001. Statistics Canada Catalogue no. 12-571-XPB.
Statistics Canada (2003c). North American Industry Classification
System - NAICS Canada, 2002. Statistics Canada Catalogue no.
12-501-XPE.
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