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- Surveys and statistical programs – Documentation: 92-370-XDescription:
Series description
This series includes five general reference products - the Preview of Products and Services; the Catalogue; the Dictionary; the Handbook and the Technical Reports - as well as geography reference products - GeoSuite and Reference Maps.
Product description
Technical Reports examine the quality of data from the 1996 Census, a large and complex undertaking. While considerable effort was taken to ensure high quality standards throughout each step, the results are subject to a certain degree of error. Each report looks at the collection and processing operations and presents results from data evaluation, as well as notes on historical comparability.
Technical Reports are aimed at moderate and sophisticated users but are written in a manner which could make them useful to all census data users. Most of the technical reports have been cancelled, with the exception of Age, Sex, Marital Status and Common-law Status, Coverage and Sampling and Weighting. These reports will be available as bilingual publications as well as being available in both official languages on the Internet as free products.
This report deals with coverage errors, which occured when persons, households, dwellings or families were missed by the 1996 Census or enumerated in error. Coverage errors are one of the most important types of error since they affect not only the accuracy of the counts of the various census universes but also the accuracy of all of the census data describing the characteristics of these universes. With this information, users can determine the risks involved in basing conclusions or decisions on census data.
Release date: 1999-12-14 - 2. Sampling and Weighting (Reference Products: Technical Reports: 1996 Census of Population) ArchivedSurveys and statistical programs – Documentation: 92-371-XDescription:
This report deals with sampling and weighting, a process whereby certain characteristics are collected and processed for a random sample of dwellings and persons identified in the complete census enumeration. Data for the whole population are then obtained by scaling up the results for the sample to the full population level. The use of sampling may lead to substantial reductions in costs and respondent burden, or alternatively, can allow the scope of a census to be broadened at the same cost.
Release date: 1999-12-07 - 3. 1996 Census Dictionary - Final Edition ArchivedSurveys and statistical programs – Documentation: 92-351-UDescription:
Series Description:
This series includes five general reference products - the Preview of Products and Services; the Catalogue; the Dictionary; the Handbook and Technical Reports - as well as two geography reference products - GeoSuite and Reference Maps.
Product Description:
The 1996 Census Dictionary provides detailed information on all of the concepts, variables and geographic elements of the 1996 Census. Information provided for each variable includes a definition, the associated census questions, applicable response categories or classifications and special remarks, namely on historical aspects. Users should make use of this edition of the 1996 Census Dictionary for the most up-to-date information. This final edition is also available on our web site as a free downloadable product.
Release date: 1999-10-25 - 4. Cycle 2 and beyond: Preparing and storing longitudinal data of the National Population Health Survey ArchivedSurveys and statistical programs – Documentation: 11-522-X19980015007Description:
The National Population Health Survey (NPHS) is a family of surveys with multiple objectives, one of which is to provide information on a panel of people who will be followed over time to reflect the dynamic process of health and illness. Data for the first cycle of the NPHS - Households Survey were collected from June 1994 to June 1995, and were released in September 1995. Data for the second cycle were collected from June 1996 to August 1997. One of the primary outputs for the second cycle is a longitudinal master file. This paper will describe six major strategies that were developed to process the longitudinal master file.
Release date: 1999-10-22 - Surveys and statistical programs – Documentation: 11-522-X19980015015Description:
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 - 6. Multilevel models for repeated binary outcomes: Attitudes and vote over the electoral cycle ArchivedSurveys and statistical programs – Documentation: 11-522-X19980015016Description:
Models for fitting longitudinal binary responses are explored using a panel study of voting intentions. A standard repeated measures multilevel logistic model is shown inadequate due to the presence of a substantial proportion of respondents who maintain a constant response over time. A multivariate binary response model is shown a better fit to the data.
Release date: 1999-10-22 - Surveys and statistical programs – Documentation: 11-522-X19980015017Description:
Longitudinal studies with repeated observations on individuals permit better characterizations of change and assessment of possible risk factors, but there has been little experience applying sophisticated models for longitudinal data to the complex survey setting. We present results from a comparison of different variance estimation methods for random effects models of change in cognitive function among older adults. The sample design is a stratified sample of people 65 and older, drawn as part of a community-based study designed to examine risk factors for dementia. The model summarizes the population heterogeneity in overall level and rate of change in cognitive function using random effects for intercept and slope. We discuss an unweighted regression including covariates for the stratification variables, a weighted regression, and bootstrapping; we also did preliminary work into using balanced repeated replication and jackknife repeated replication.
Release date: 1999-10-22 - Surveys and statistical programs – Documentation: 11-522-X19980015018Description:
This paper presents a method for handling longitudinal data in which individuals belong to more than one unit at a higher level, and also where there is missing information on the identification of the units to which they belong. In education, for example, a student might be classified as belonging sequentially to a particular combination of primary and secondary school, but for some students, the identity of either the primary or secondary school may be unknown. Likewise, in a longitudinal study, students may change school or class from one period to the next, so 'belonging' to more than one higher level unit. The procedures used to model these stuctures are extensions of a random effects cross-classified multilevel model.
Release date: 1999-10-22 - Surveys and statistical programs – Documentation: 11-522-X19980015019Description:
The British Labour Force Survey (LFS) is a quarterly household survey with a rotating sample design that can potentially be used to produce longitudinal data, including estimates of labour force gross flows. However, these estimates may be biased due to the effect of non-response. Weighting adjustments are a commonly used method to account for non-response bias. We find that weighting may not fully account for the effect of non-response bias because non-response may depend on the unobserved labour force flows, i.e., the non-response is non-ignorable. To adjust for the effects of non-ignorable non-response, we propose a model for the complex non-response patterns in the LFS which controls for the correlated within-household non-response behaviour found in the survey. The results of modelling suggest that non-response may be non-ignorable in the LFS, causing the weighting estimates to be biased.
Release date: 1999-10-22 - Surveys and statistical programs – Documentation: 11-522-X19980015020Description:
At the end of 1993, Eurostat lauched a 'community' panel of households. The first wave, carried out in 1994 in the 12 countries of the European Union, included some 7,300 households in France, and at least 14,000 adults 17 years or over. Each individual was then followed up and interviewed each year, even if they had moved. The individuals leaving the sample present a particular profile. In the first part, we present a sketch of how our sample evolves and an analysis of the main characteristics of the non-respondents. We then propose 2 models to correct for non-response per homogeneous category. We then describe the longitudinal weight distribution obtained from the two models, and the cross-sectional weights using the weight share method. Finally, we compare some indicators calculated using both weighting methods.
Release date: 1999-10-22
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Reference (44)
Reference (44) (0 to 10 of 44 results)
- Surveys and statistical programs – Documentation: 92-370-XDescription:
Series description
This series includes five general reference products - the Preview of Products and Services; the Catalogue; the Dictionary; the Handbook and the Technical Reports - as well as geography reference products - GeoSuite and Reference Maps.
Product description
Technical Reports examine the quality of data from the 1996 Census, a large and complex undertaking. While considerable effort was taken to ensure high quality standards throughout each step, the results are subject to a certain degree of error. Each report looks at the collection and processing operations and presents results from data evaluation, as well as notes on historical comparability.
Technical Reports are aimed at moderate and sophisticated users but are written in a manner which could make them useful to all census data users. Most of the technical reports have been cancelled, with the exception of Age, Sex, Marital Status and Common-law Status, Coverage and Sampling and Weighting. These reports will be available as bilingual publications as well as being available in both official languages on the Internet as free products.
This report deals with coverage errors, which occured when persons, households, dwellings or families were missed by the 1996 Census or enumerated in error. Coverage errors are one of the most important types of error since they affect not only the accuracy of the counts of the various census universes but also the accuracy of all of the census data describing the characteristics of these universes. With this information, users can determine the risks involved in basing conclusions or decisions on census data.
Release date: 1999-12-14 - 2. Sampling and Weighting (Reference Products: Technical Reports: 1996 Census of Population) ArchivedSurveys and statistical programs – Documentation: 92-371-XDescription:
This report deals with sampling and weighting, a process whereby certain characteristics are collected and processed for a random sample of dwellings and persons identified in the complete census enumeration. Data for the whole population are then obtained by scaling up the results for the sample to the full population level. The use of sampling may lead to substantial reductions in costs and respondent burden, or alternatively, can allow the scope of a census to be broadened at the same cost.
Release date: 1999-12-07 - 3. 1996 Census Dictionary - Final Edition ArchivedSurveys and statistical programs – Documentation: 92-351-UDescription:
Series Description:
This series includes five general reference products - the Preview of Products and Services; the Catalogue; the Dictionary; the Handbook and Technical Reports - as well as two geography reference products - GeoSuite and Reference Maps.
Product Description:
The 1996 Census Dictionary provides detailed information on all of the concepts, variables and geographic elements of the 1996 Census. Information provided for each variable includes a definition, the associated census questions, applicable response categories or classifications and special remarks, namely on historical aspects. Users should make use of this edition of the 1996 Census Dictionary for the most up-to-date information. This final edition is also available on our web site as a free downloadable product.
Release date: 1999-10-25 - 4. Cycle 2 and beyond: Preparing and storing longitudinal data of the National Population Health Survey ArchivedSurveys and statistical programs – Documentation: 11-522-X19980015007Description:
The National Population Health Survey (NPHS) is a family of surveys with multiple objectives, one of which is to provide information on a panel of people who will be followed over time to reflect the dynamic process of health and illness. Data for the first cycle of the NPHS - Households Survey were collected from June 1994 to June 1995, and were released in September 1995. Data for the second cycle were collected from June 1996 to August 1997. One of the primary outputs for the second cycle is a longitudinal master file. This paper will describe six major strategies that were developed to process the longitudinal master file.
Release date: 1999-10-22 - Surveys and statistical programs – Documentation: 11-522-X19980015015Description:
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 - 6. Multilevel models for repeated binary outcomes: Attitudes and vote over the electoral cycle ArchivedSurveys and statistical programs – Documentation: 11-522-X19980015016Description:
Models for fitting longitudinal binary responses are explored using a panel study of voting intentions. A standard repeated measures multilevel logistic model is shown inadequate due to the presence of a substantial proportion of respondents who maintain a constant response over time. A multivariate binary response model is shown a better fit to the data.
Release date: 1999-10-22 - Surveys and statistical programs – Documentation: 11-522-X19980015017Description:
Longitudinal studies with repeated observations on individuals permit better characterizations of change and assessment of possible risk factors, but there has been little experience applying sophisticated models for longitudinal data to the complex survey setting. We present results from a comparison of different variance estimation methods for random effects models of change in cognitive function among older adults. The sample design is a stratified sample of people 65 and older, drawn as part of a community-based study designed to examine risk factors for dementia. The model summarizes the population heterogeneity in overall level and rate of change in cognitive function using random effects for intercept and slope. We discuss an unweighted regression including covariates for the stratification variables, a weighted regression, and bootstrapping; we also did preliminary work into using balanced repeated replication and jackknife repeated replication.
Release date: 1999-10-22 - Surveys and statistical programs – Documentation: 11-522-X19980015018Description:
This paper presents a method for handling longitudinal data in which individuals belong to more than one unit at a higher level, and also where there is missing information on the identification of the units to which they belong. In education, for example, a student might be classified as belonging sequentially to a particular combination of primary and secondary school, but for some students, the identity of either the primary or secondary school may be unknown. Likewise, in a longitudinal study, students may change school or class from one period to the next, so 'belonging' to more than one higher level unit. The procedures used to model these stuctures are extensions of a random effects cross-classified multilevel model.
Release date: 1999-10-22 - Surveys and statistical programs – Documentation: 11-522-X19980015019Description:
The British Labour Force Survey (LFS) is a quarterly household survey with a rotating sample design that can potentially be used to produce longitudinal data, including estimates of labour force gross flows. However, these estimates may be biased due to the effect of non-response. Weighting adjustments are a commonly used method to account for non-response bias. We find that weighting may not fully account for the effect of non-response bias because non-response may depend on the unobserved labour force flows, i.e., the non-response is non-ignorable. To adjust for the effects of non-ignorable non-response, we propose a model for the complex non-response patterns in the LFS which controls for the correlated within-household non-response behaviour found in the survey. The results of modelling suggest that non-response may be non-ignorable in the LFS, causing the weighting estimates to be biased.
Release date: 1999-10-22 - Surveys and statistical programs – Documentation: 11-522-X19980015020Description:
At the end of 1993, Eurostat lauched a 'community' panel of households. The first wave, carried out in 1994 in the 12 countries of the European Union, included some 7,300 households in France, and at least 14,000 adults 17 years or over. Each individual was then followed up and interviewed each year, even if they had moved. The individuals leaving the sample present a particular profile. In the first part, we present a sketch of how our sample evolves and an analysis of the main characteristics of the non-respondents. We then propose 2 models to correct for non-response per homogeneous category. We then describe the longitudinal weight distribution obtained from the two models, and the cross-sectional weights using the weight share method. Finally, we compare some indicators calculated using both weighting methods.
Release date: 1999-10-22
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