National Longitudinal Survey of Children and Youth (NLSCY)

Status:
Inactive
Frequency:
Biennial
Record number:
4450

The National Longitudinal Survey of Children and Youth (NLSCY) is a long-term study of Canadian children that follows their development and well-being from birth to early adulthood. The study is designed to collect information about factors influencing a child's social, emotional and behavioural development and to monitor the impact of these factors on the child's development over time.

Detailed information for 1998-1999 (Cycle 3)

Data release - December 19, 2000

Description

The National Longitudinal Survey of Children and Youth (NLSCY) is a long-term study of Canadian children that follows their development and well-being from birth to early adulthood. The NLSCY began in 1994 and is jointly conducted by Statistics Canada and Human Resources and Skills Development Canada (HRSDC), formerly known as Human Resources Development Canada (HRDC).

The study is designed to collect information about factors influencing a child's social, emotional and behavioural development and to monitor the impact of these factors on the child's development over time.

The survey covers a comprehensive range of topics including the health of children, information on their physical development, learning and behaviour as well as data on their social environment (family, friends, schools and communities).

Information from the NLSCY is being used by a variety of people at all levels of government, at universities, and policy-making organizations.

Subjects

  • Child development and behaviour
  • Children and youth
  • Education
  • Education, training and learning
  • Health and well-being (youth)

Data sources and methodology

Target population

The target population comprises the non-institutionalized civilian population (aged 0 to 11 at the time of their selection) in Canada's 10 provinces. The survey excludes children living on Indian reserves or Crown lands, residents of institutions, full-time members of the Canadian Armed Forces, and residents of some remote regions.

Instrument design

All questionnaires were developed in coordination with HRSDC and an expert advisory group. All instruments were tested in focus groups and pilot surveys prior to collection.

Sampling

This is a sample survey with a longitudinal design.

The NLSCY sample consists of a longitudinal sample and a cross-sectional sample.

The longitudinal sample is made up of three cohorts. The first cohort comprises children aged 0 to 11 at the time of their selection in 1994. They will remain in the survey until they reach the age of 25. The second cohort consists of children aged 0 to 1 at the time of their selection in 1996. They will remain in the survey until they reach the age of 5. The third cohort is made up of children aged 0 to 1 at the time of their selection in 1998. They too will remain in the survey until they reach the age of 5.

The 0-1 longitudinal and cross-sectional samples were drawn from Labour Force Survey (LFS) respondent households. The one-year-olds in cohort 3 were selected from the Birth Register (BR) because the LFS did not have enough eligible children to meet the survey's needs. For the purpose of selecting children from the BR, each province is divided into urban and rural strata. A simple random sample is selected in the rural stratum, and a two-stage design is used in the urban strata. A sample of geographic areas is drawn first, and then a sample of children is drawn from within the selected areas.

Data sources

Data collection for this reference period: 1998-09-01 to 1999-06-30

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

Data collection has two components: computer-assisted telephone interviewing (CATI) and computer-assisted personal interviewing (CAPI).

CATI is used for children aged 0 to 3, and CAPI is used for older children. In all cases, the person who knows the child best is interviewed (usually a parent). Depending on the child's age, there are other components requiring his/her participation, such as mathematics and aptitude tests and a self-administered questionnaire. For school-age children, the teacher and the school principal are also asked to complete questionnaires.

View the Questionnaire(s) and reporting guide(s).

Error detection

From data collection to weighting, checks are performed to detect errors. For collection, inconsistency checks are programmed into the data entry application. More sophisticated checks are carried out later during data processing. Further checks are performed when the data are weighted. These checks serve to detect both cross-sectional and longitudinal inconsistencies.

Imputation

For partial non-response, only household, youth and PMK incomes are imputed, by the historical method whenever possible, or else by the hot-deck method.

For other variables, a non-response code is assigned to the missing variables.

In the case of total non-response, the weights are adjusted.

Estimation

Longitudinal cohorts: The initial weight from the preceding cycle is used. For non-response adjustment, response groups are formed using the previous cycle's variables. The sample is post-stratified by province, age and sex on the basis of population totals at the time of selection The bootstrap method is used to calculate the variance.

Cross-sectional cohorts: The initial weight is the LFS subweight or the inverse selection probability for the Birth Register. For LFS children, adjustments are made for the number of rotation groups, non-response based on geographic groupings, multiple economic families and the number of eligible children. The longitudinal and cross-sectional portions are combined with a composite alpha at the provincial level. The sample is post-stratified on the basis of the population totals. The bootstrap method is used to calculate the variance.

Users are also provided with approximate coefficient-of-variation tables.

Quality evaluation

Various analyses are performed to determine whether the survey data meet the initial objectives. Among them are coverage and non-response analyses. Adjustments are also made for the non-random nature of non-response. In addition, consistency checks are performed.

Disclosure control

Statistics Canada is prohibited by law from releasing any data which would divulge information obtained under the Statistics Act that relates to any identifiable person, business or organization without the prior knowledge or the consent in writing of that person, business or organization. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. Suppression of direct identifiers (name, address, etc.) and indirect identifiers (combination of variables identifying a respondent) is used.

Confidentiality checks are performed at the family level.

Before tables are published, steps are taken to ensure that there is a minimum number of units in each cell and that the coefficient of variation is low enough for the data to be published.

******************************************
The Quebec Institute of Statistics is engaged in a study of child development called the Quebec Longitudinal Study of Child Development (QLSCD). Past respondents of the National Longitudinal Survey of Children and Youth (NLSCY) are being asked to participate in the QLSCD. NLSCY respondents are being contacted in January and February 2010 to obtain their permission to release their contact information and collected survey data to the Québec Institute of Statistics.

Data accuracy

A set of Excel spreadsheets, with a user-friendly Visual Basic interface, is available to users to obtain approximate sampling variances of proportions. SAS and SPSS macros have also been developed to calculate the sampling variance of an estimate using Bootstrap weights. These macros and spreadsheets are available at Statistics Canada Research Data Centres (RDCs).

Users should keep in mind that the NLSCY is a general population survey and not designed for the analysis of rare characteristics or rare subpopulations within NLSCY which would yield small samples and result in high relative sampling variance.

Possible sources of nonsampling errors in the NLSCY include: response errors due to sensitive questions, poor memory, translated questionnaires, approximate answers, and conditioning bias; nonresponse errors; and coverage errors.

In the case of nonresponse errors, weight adjustments are performed to minimize the effect of bias due to total nonresponse. Some longitudinal respondents do not participate in every cycle. This is cycle non-response. When dealing with the longitudinal data for a respondent, data from every cycle is not necessarily available. For example, a child may be a respondent in Cycles, 1, 3, 4, and 5, but not Cycle 2. If data from every cycle is crucial, the analyst can limit himself to children without cycle non-response and use the longitudinal weights for this group, variable EWTCWd1L.

Regarding partial nonresponse, imputation is performed on the following variables: adult income, youth income, household income, adult labour force, and Motor and Social Development items.

In the case of coverage errors, the longitudinal and cross-sectional weights are post-stratified to population counts to minimize coverage bias. The NLSCY uses multiple frames, the main one being the Labour Force Survey's samples. Sources of coverage error arising from the use of the LFS include: only LFS respondents are selected by the NLSCY sample; and the NLSCY sample is selected based on the household's composition at the time of the LFS interview.

In Cycle 3, provincial birth registry data were used to sample one year-olds born in 1997, consequently one year olds born outside of Canada in 1997 were excluded; and some births may not have been registered until after the sample was selected.

The NLSCY has non-uniform coverage of children, by month of birth, for births in 1997 and 1998: it excludes births in January, February, March or April of 1997; and for children born in 1998, births in January, February and March are overrepresented.

Documentation

Data file