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All (4)

All (4) ((4 results))

  • 1. Estimation of research and development expenditures in the higher education sector, 2000-2001 Archived
    Stats in brief: 88-001-X20020067892
    Description:

    Institutions in the higher education sector usually have records of funds received by them specifically for research and development , and some can provide lists of research projects carried out by staff. The research and development expenditure estimates are based on reports of payments awarded to institutions through the annual survey of the Canadian Association of University Business Officers (CAUBO).

    Release date: 2002-11-27
  • 2. Nonresponse bias analyses at the National Center for Education Statistics Archived
    Surveys and statistical programs – Documentation: 11-522-X20010016269
    Description:

    This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.

    In surveys with low response rates, non-response bias can be a major concern. While it is not always possible to measure the actual bias due to non-response, there are different approaches that help identify potential sources of non-response bias. In the National Center for Education Statistics (NCES), surveys with a response rate lower than 70% must conduct a non-response bias analysis. This paper discusses the different approaches to non-response bias analyses using examples from NCES.

    Release date: 2002-09-12
  • 3. Too Far to Go on? Distance to School and University Participation Archived
    Articles and reports: 11F0019M2002191
    Geography: Canada
    Description:

    This study assesses how geographic distance between home and school affects the probability of attending university shortly after high school graduation. Students that grow up near a university can save on costs by staying home to attend the local university and thus may be more likely to attend. Using the Survey of Labour and Income Dynamics, a database of Canadian university postal codes and a special postal code conversion file that calculates the geographic co-ordinates of postal codes, it was possible to estimate the straight-line distances between the homes of high school students prior to graduating and the nearest university. After controlling for family income, parental education and other factors associated with university participation, students living 'out-of-commuting distance' are far less likely to attend than are students living 'within commuting distance.' Distance also plays a role in the relationship between university participation and its other correlates, such as family income and sex.

    Release date: 2002-06-24
  • 4. Ontario Grade 3 student achievement Archived
    Articles and reports: 11-008-X20020016197
    Geography: Province or territory
    Description:

    This study identifies factors that influenced Ontario Grade 3 student achievement using a reference group to assess the impact of changes in student, class and school characteristics.

    Release date: 2002-06-11
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Analysis (3)

Analysis (3) ((3 results))

  • 1. Estimation of research and development expenditures in the higher education sector, 2000-2001 Archived
    Stats in brief: 88-001-X20020067892
    Description:

    Institutions in the higher education sector usually have records of funds received by them specifically for research and development , and some can provide lists of research projects carried out by staff. The research and development expenditure estimates are based on reports of payments awarded to institutions through the annual survey of the Canadian Association of University Business Officers (CAUBO).

    Release date: 2002-11-27
  • 2. Too Far to Go on? Distance to School and University Participation Archived
    Articles and reports: 11F0019M2002191
    Geography: Canada
    Description:

    This study assesses how geographic distance between home and school affects the probability of attending university shortly after high school graduation. Students that grow up near a university can save on costs by staying home to attend the local university and thus may be more likely to attend. Using the Survey of Labour and Income Dynamics, a database of Canadian university postal codes and a special postal code conversion file that calculates the geographic co-ordinates of postal codes, it was possible to estimate the straight-line distances between the homes of high school students prior to graduating and the nearest university. After controlling for family income, parental education and other factors associated with university participation, students living 'out-of-commuting distance' are far less likely to attend than are students living 'within commuting distance.' Distance also plays a role in the relationship between university participation and its other correlates, such as family income and sex.

    Release date: 2002-06-24
  • 3. Ontario Grade 3 student achievement Archived
    Articles and reports: 11-008-X20020016197
    Geography: Province or territory
    Description:

    This study identifies factors that influenced Ontario Grade 3 student achievement using a reference group to assess the impact of changes in student, class and school characteristics.

    Release date: 2002-06-11
Reference (1)

Reference (1) ((1 result))

  • 1. Nonresponse bias analyses at the National Center for Education Statistics Archived
    Surveys and statistical programs – Documentation: 11-522-X20010016269
    Description:

    This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.

    In surveys with low response rates, non-response bias can be a major concern. While it is not always possible to measure the actual bias due to non-response, there are different approaches that help identify potential sources of non-response bias. In the National Center for Education Statistics (NCES), surveys with a response rate lower than 70% must conduct a non-response bias analysis. This paper discusses the different approaches to non-response bias analyses using examples from NCES.

    Release date: 2002-09-12
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