The Youth in Transition Survey (YITS) is a longitudinal survey undertaken jointly by Statistics Canada and Human Resources and Skills Development Canada. This survey is designed to examine the major transitions in the lives of youth, particularly between education, training and work.
Data release – January 23, 2002
The Youth in Transition Survey (YITS) is designed to examine the patterns of, and influences on, major transitions in young people's lives, particularly with respect to education, training and work. Human Resources and Skills Development Canada and Statistics Canada have been developing the YITS in consultation with provincial and territorial ministries and departments of labour and education. Content includes measurement of major transitions in young people's lives including virtually all formal educational experiences and most labour market experiences, achievement, aspirations and expectations, and employment experiences.
The results from the Youth in Transition Survey will have many uses. Human Resources and Skills Development Canada will use them to aid policy and program development. Other users of the results include educators, social and policy analysts, and advocacy groups. The information will show how young adults are making their critical transitions into their adult years.
These researchers and analysts will have access to important information that can be used in developing programs to deal with both short-term and long-term problems or barriers that young adults may face in their pursuit of higher education or in gaining work experience. Information from the survey will help to evaluate the effectiveness of existing programs and practices, to determine the most appropriate age at which to introduce programs, and to better target programs to those most in need.
Young adults themselves will be able to see the impact of decisions relating to education or work experiences. They will be able to see how their own experiences compare to those of other young adults.
The survey population for the 18 to 20 year-old cohort includes persons born in the years 1979 to 1981. Geographically, the target population excludes the northern territories, Indian reserves, Canadian Forces bases and some remote areas.
The questionnaire specifications were developed in coordination with our client Human Resources and Skills Development Canada (HRSDC), formerly Human Resources Development Canada (HRDC) and an expert advisory group.
The questionnaire was designed for a Computer Assisted Telephone Interview (CATI). As module specifications were written, the associated logical flows into and out of the questions were programmed. This included specifying the type of answer required, the minimum and maximum values, hard and soft on-line edits associated with the questions and what was required in case of non-response. The initial version of the questionnaire was focus-group tested. The questionnaire was programmed in CASES (the software used to develop CATI applications) module by module initially. During this process client divisions tested each module for text spelling and grammar; flows, ranges, acceptance of all true values, as well as the assignment of proper in-progress and final codes. A pilot survey was held and, following that, revisions were made to the question specifications and the program for the main survey.
This is a sample survey with a longitudinal design.
Factors such as the high mobility rate of the 18-20 age group and its relatively low incidence at the household level led to a stratified multi-stage sample design based on the use of the Labour Force Survey sample, drawing from currently active and rotate-out households. Within each household, one person in the target population was pre-selected for YITS. The initial sample size was 29,000 persons.
Data collection for this reference period: 2000-01-01 – 2000-03-31
Responding to this survey is voluntary.
Data are collected directly from survey respondents.
Data collection for cycle 1 of the 18 to 20 year-old cohort was administered from January to March 2000, via computer-assisted telephone interview (CATI). Interviews were completed with 23,000 youth.
A series of verifications took place to ensure that the records were consistent and that collection and capture of the data did not introduce errors. Reported data were examined for completeness and consistency using automated edits coupled with manual review. Some responses reporting uncommon values or characteristics were processed manually. For quantitative data, outliers -- unusually large (or small) values -- were identified and carefully looked at to assess if they were valid data.
For quantitative variables such as income and earnings, imputation was performed to treat missing responses and/or outliers. The first step in the imputation process was a within-record imputation where missing information was replaced with values derived from the respondent's answer to other questions in the questionnaire using deterministic edit rules. The remaining missing data were imputed using nearest-neighbour donor imputation. Impudon was used for donor imputation.
Impudon is a generalized system for donor imputation built as a SAS macro using the version number 8 of SAS. It manages both numeric (positive, zero, negative) and categorical (or character) variables; uses matching fields that can be numeric and/or categorical; can use weights for relativizing the matching fields in the distance function between a recipient and a donor. There are many criteria of distance that can be used, and the user can specify more than one in an Impudon execution. The imputation groups are automatically generated from a variable list. The post-imputation edit rules can be of any type (linear, non linear, conditional, applying boolean operators, on numeric and/or categorical variables).
The estimation of population characteristics from a survey is based on the premise that each sampled unit represents, in addition to itself, a certain number of non-sampled units in the population. A basic survey weight is attached to each record to indicate the number of units in the population that are represented by that unit in the sample. This basic weight is derived from the sample design.
Because the sample for the YITS 18-20 year-old cohort is derived from households that were in the LFS sample, part of the LFS weighting procedure is applicable to the YITS sample. More precisely, the LFS sub-weight is used as the initial weight for the YITS sample units. This weight represents the inverse of the probability of dwelling selection for the LFS, adjusted for LFS non-response.
To reflect the YITS sample design and take into account the non-response for this survey, several adjustments must be applied to the LFS sub-weight to derive the YITS final weight. In total, five adjustments are required to compensate for:
1. including 36 groups from the LFS
2. a priori non-response at the household level
3. selecting one person per household
4. non-response of the YITS selected persons
5. differences between post-censal demographic estimates and the weighted counts derived from the first four adjustments
Labour Force Survey (LFS) rotation groups were used (both active and inactive) in selecting the sample. During collection it was found that the older the rotation group, the harder it was to find the respondents, which translated in a lower response rate for the older groups. This was taken into consideration at the weighting stage.
Statistics Canada is prohibited by law from releasing any information it collects which could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.
Data quality is affected by both sampling and non-sampling errors. Non-sampling errors were minimized through testing (focus group, pilot survey and main survey); training of regional office staff; observation by head office personnel; tabulations of initial data; and adjustment of questionnaire specifications for future cycles. Quality assurance measures were implemented at each step of the data collection and processing cycle to monitor data quality. For sampling error, data reliability guidelines were established based on coefficient of variation (CV). It is recommended that any estimate based on fewer than 30 observations or with a CV greater than 33.3% not be released.