Response and nonresponse

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  • 1. Estimating labour force gross flows from surveys subject to household-level nonignorable nonresponse Archived
    Articles and reports: 12-001-X19980024349
    Description:

    Measurement of gross flows in labour force status is an important objective of the continuing labour force surveys carried out by many national statistics agencies. However, it is well known that estimation of these flows can be complicated by nonresponse, measurement errors, sample rotation and complex design effects. Motivated by nonresponse patterns in household-based surveys, this paper focuses on estimation of labour force gross flows, while simultaneously adjusting for nonignorable nonresponse. Previous model-based approaches to gross flows estimation have assumed nonresponse to be an individual-level process. We propose a class of models that allow for nonignorable household-level nonresponse. A simulation study is used to show, that individual-level labour force gross flows estimates from household-based survey data, may be biased and that estimates using household-level models can offer a reduction in this bias.

    Release date: 1999-01-14
  • 2. Treatment of nonresponse in cycle two of the National Population Health Survey Archived
    Articles and reports: 12-001-X19980024352
    Description:

    The National Population Health Survey (NPHS) is one of Statistics Canada's three major longitudinal household surveys providing an extensive coverage of the Canadian population. A panel of approximately 17,000 people are being followed up every two years for up to twenty years. The survey data are used for longitudinal analyses, although an important objective is the production of cross-sectional estimates. Each cycle panel respondents provide detailed health information (H) while, to augment the cross-sectional sample, general socio-demographic and health information (G) are collected from all members of their households. This particular collection strategy presents several observable response patterns for Panel Members after two cycles: GH-GH, GH-G*, GH-**, G*-GH, G*-G* and G*-**, where "*" denotes a missing portion of data. The article presents the methodology developed to deal with these types of longitudinal nonresponse as well as with nonresponse from a cross-sectional perspective. The use of weight adjustments for nonresponse and the creation of adjustment cells for weighting using a CHAID algorithm are discussed.

    Release date: 1999-01-14
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  • 1. Estimating labour force gross flows from surveys subject to household-level nonignorable nonresponse Archived
    Articles and reports: 12-001-X19980024349
    Description:

    Measurement of gross flows in labour force status is an important objective of the continuing labour force surveys carried out by many national statistics agencies. However, it is well known that estimation of these flows can be complicated by nonresponse, measurement errors, sample rotation and complex design effects. Motivated by nonresponse patterns in household-based surveys, this paper focuses on estimation of labour force gross flows, while simultaneously adjusting for nonignorable nonresponse. Previous model-based approaches to gross flows estimation have assumed nonresponse to be an individual-level process. We propose a class of models that allow for nonignorable household-level nonresponse. A simulation study is used to show, that individual-level labour force gross flows estimates from household-based survey data, may be biased and that estimates using household-level models can offer a reduction in this bias.

    Release date: 1999-01-14
  • 2. Treatment of nonresponse in cycle two of the National Population Health Survey Archived
    Articles and reports: 12-001-X19980024352
    Description:

    The National Population Health Survey (NPHS) is one of Statistics Canada's three major longitudinal household surveys providing an extensive coverage of the Canadian population. A panel of approximately 17,000 people are being followed up every two years for up to twenty years. The survey data are used for longitudinal analyses, although an important objective is the production of cross-sectional estimates. Each cycle panel respondents provide detailed health information (H) while, to augment the cross-sectional sample, general socio-demographic and health information (G) are collected from all members of their households. This particular collection strategy presents several observable response patterns for Panel Members after two cycles: GH-GH, GH-G*, GH-**, G*-GH, G*-G* and G*-**, where "*" denotes a missing portion of data. The article presents the methodology developed to deal with these types of longitudinal nonresponse as well as with nonresponse from a cross-sectional perspective. The use of weight adjustments for nonresponse and the creation of adjustment cells for weighting using a CHAID algorithm are discussed.

    Release date: 1999-01-14
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