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  • 1. Recent development of software to analyse longitudinal studies: Examples from the Office for National Statistics Longitudinal Study Archived
    Surveys and statistical programs – Documentation: 11-522-X19980015015
    Description:

    In epidemiology analysis of longitudinal data is commonly accepted as providing the most robust measures of association between putative risk and selected outcomes such as death or cancer. SMARTIE is a SAS application for efficient analysis of longitudinal data. Based on person days at risk, it can handle multiple exits from and re-entries to risk, and derives outcome measures such as survival rates. Standardised Mortality Ratios (SMRs) and Cancer Incidence Ratios (SIRs). Summary data can be produced in a format easily ported to any modelling package such as Stats 5.0. We discuss the background to its development, the overall program structure, its command language, and finally we say something about the organization of outputs. Findings from survival studies using the Longitudinal Study of the Office for National Statistics (ONS) are used to demonstrate features of SMARTIE. This study is based on one per cent of the population of England and Wales. It is continually updated with the addition of new members and with information from birth, death and cancer records, and from the census.

    Release date: 1999-10-22
  • 2. Statistics Canada's Measurement and Valuation of Unpaid Work Archived
    Surveys and statistical programs – Documentation: 71F0023X1999001
    Description:

    This paper is an overview of the activities undertaken by Statistics Canada over the past several decades in the field of measuring and valuing unpaid work in all of its many forms. It was first prepared in the early 1990s when the Agency's accomplishments in the field of unpaid work were not as widely known as Statistics Canada would have liked. With each significant new achievement of the Agency, this note has been updated and further updates will be produced in step with the Agency's continuing outputs in this important area.

    Release date: 1999-01-28
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  • 1. Recent development of software to analyse longitudinal studies: Examples from the Office for National Statistics Longitudinal Study Archived
    Surveys and statistical programs – Documentation: 11-522-X19980015015
    Description:

    In epidemiology analysis of longitudinal data is commonly accepted as providing the most robust measures of association between putative risk and selected outcomes such as death or cancer. SMARTIE is a SAS application for efficient analysis of longitudinal data. Based on person days at risk, it can handle multiple exits from and re-entries to risk, and derives outcome measures such as survival rates. Standardised Mortality Ratios (SMRs) and Cancer Incidence Ratios (SIRs). Summary data can be produced in a format easily ported to any modelling package such as Stats 5.0. We discuss the background to its development, the overall program structure, its command language, and finally we say something about the organization of outputs. Findings from survival studies using the Longitudinal Study of the Office for National Statistics (ONS) are used to demonstrate features of SMARTIE. This study is based on one per cent of the population of England and Wales. It is continually updated with the addition of new members and with information from birth, death and cancer records, and from the census.

    Release date: 1999-10-22
  • 2. Statistics Canada's Measurement and Valuation of Unpaid Work Archived
    Surveys and statistical programs – Documentation: 71F0023X1999001
    Description:

    This paper is an overview of the activities undertaken by Statistics Canada over the past several decades in the field of measuring and valuing unpaid work in all of its many forms. It was first prepared in the early 1990s when the Agency's accomplishments in the field of unpaid work were not as widely known as Statistics Canada would have liked. With each significant new achievement of the Agency, this note has been updated and further updates will be produced in step with the Agency's continuing outputs in this important area.

    Release date: 1999-01-28
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