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  • Articles and reports: 12-001-X201100111444
    Description:

    Data linkage is the act of bringing together records that are believed to belong to the same unit (e.g., person or business) from two or more files. It is a very common way to enhance dimensions such as time and breadth or depth of detail. Data linkage is often not an error-free process and can lead to linking a pair of records that do not belong to the same unit. There is an explosion of record linkage applications, yet there has been little work on assuring the quality of analyses using such linked files. Naively treating such a linked file as if it were linked without errors will, in general, lead to biased estimates. This paper develops a maximum likelihood estimator for contingency tables and logistic regression with incorrectly linked records. The estimation technique is simple and is implemented using the well-known EM algorithm. A well known method of linking records in the present context is probabilistic data linking. The paper demonstrates the effectiveness of the proposed estimators in an empirical study which uses probabilistic data linkage.

    Release date: 2011-06-29

  • Articles and reports: 11-522-X200800010975
    Description:

    A major issue in official statistics is the availability of objective measures supporting the based-on-fact decision process. Istat has developed an Information System to assess survey quality. Among other standard quality indicators, nonresponse rates are systematically computed and stored for all surveys. Such a rich information base permits analysis over time and comparisons among surveys. The paper focuses on the analysis of interrelationships between data collection mode and other survey characteristics on total nonresponse. Particular attention is devoted to the extent to which multi-mode data collection improves response rates.

    Release date: 2009-12-03

  • Articles and reports: 11-522-X200800011003
    Description:

    This study examined the feasibility of developing correction factors to adjust self-reported measures of Body Mass Index to more closely approximate measured values. Data are from the 2005 Canadian Community Health Survey where respondents were asked to report their height and weight and were subsequently measured. Regression analyses were used to determine which socio-demographic and health characteristics were associated with the discrepancies between reported and measured values. The sample was then split into two groups. In the first, the self-reported BMI and the predictors of the discrepancies were regressed on the measured BMI. Correction equations were generated using all predictor variables that were significant at the p<0.05 level. These correction equations were then tested in the second group to derive estimates of sensitivity, specificity and of obesity prevalence. Logistic regression was used to examine the relationship between measured, reported and corrected BMI and obesity-related health conditions. Corrected estimates provided more accurate measures of obesity prevalence, mean BMI and sensitivity levels. Self-reported data exaggerated the relationship between BMI and health conditions, while in most cases the corrected estimates provided odds ratios that were more similar to those generated with the measured BMI.

    Release date: 2009-12-03

  • Articles and reports: 11-522-X20050019473
    Description:

    This talk will provide a brief overview of some of some techniques, highlighting the advantages and disadvantages of each, with particular reference to the data types usually encountered in the social sciences. The overview will touch on naïve methods based on the use of latent variable scores, and on methods for correcting and / or avoiding the biases associated with such analyses. The talk will conclude with a brief description of some recent applications to probit and logistic regression with latent predictor variables, and with suggestions for future research.

    Release date: 2007-03-02

  • Articles and reports: 11-522-X20030017595
    Geography: Canada
    Description:

    This paper discusses challenges faced in locating recent immigrants and implementing strategies to increase response rates for the Longitudinal Survey of Immigrants to Canada (LSIC). It also presents a model-assisted technique for adjusting for non-response, based on the approach proposed by Eltinge-Yanseneh to define adjustment classes.

    Release date: 2005-01-26

  • Articles and reports: 11-522-X20030017598
    Description:

    This paper looks at descriptive statistics to evaluate non-response in the Labour Force Survey (LFS) and also at ways of improving the current methodology of making non-response adjustments.

    Release date: 2005-01-26

  • Articles and reports: 12-001-X20030026777
    Description:

    The Accuracy and Coverage Evaluation survey was conducted to estimate the coverage in the 2000 U.S. Census. After field procedures were completed, several types of missing data had to be addressed to apply dual-system estimation. Some housing units were not interviewed. Two noninterview adjustments were devised from the same set of interviews, one for each of two points in time. In addition, the resident, match, or enumeration status of some respondents was not determined. Methods applied in the past were replaced to accommodate a tighter schedule to compute and verify the estimates. This paper presents the extent of missing data in the survey, describes the procedures applied, comparing them to past and current alternatives, and provides analytical summaries of the procedures, including comparisons of dual-system estimates of population under alternatives. Because the resulting levels of missing data were low, it appears that alternative procedures would not have affected the results substantially. However some changes in the estimates are noted.

    Release date: 2004-01-27

  • Articles and reports: 12-001-X20010026097
    Description:

    A compositional time series is defined as a multivariate time series in which each of the series has values bounded between zero and one and the sum of the series equals one at each time point. Data with such characteristics are observed in repeated surveys when a survey variable has a multinomial response but interest lies in the proportion of units classified in each of its categories. In this case, the survey estimates are proportions of a whole subject to a unity-sum constraint. In this paper we employ a state space approach for modelling compositional time series from repeated surveys taking into account the sampling errors. The additive logistic transformation is used in order to guarantee predictions and signal estimates bounded between zero and one which satisfy the unity-sum constraint. The method is applied to compositional data from the Brazilian Labour Force Survey. Estimates of the vector of proportions and the unemployment rate are obtained. In addition, the structural components of the signal vector, such as the seasonals and the trends, are produced.

    Release date: 2002-02-28

  • Articles and reports: 12-001-X20010015858
    Description:

    The objective of this paper is to study and measure the change (from the initial to the final weight) which results from the procedure used to modify weights. A breakdown of the final weights is proposed in order to evaluate the relative impact of the nonresponse adjustment, the correction for poststratification and the interaction between these two adjustments. This measure of change is used as a tool for comparing the effectiveness of the various methods for adjusting for nonresponse, in particular the methods relying on the formation of Response Homogeneity Groups. The measure of change is examined through a simulation study, which uses data from a Statistics Canada longitudinal survey, the Survey of Labour and Income Dynamics. The measure of change is also applied to data obtained from a second longitudinal survey, the National Longitudinal Survey of Children and Youth.

    Release date: 2001-08-22

  • Articles and reports: 81-003-X19990045143
    Geography: Canada
    Description:

    This article explores regional differences among students who drop out of Canadian universities and community colleges.

    Release date: 2000-09-01
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Analysis (17)

Analysis (17) (0 to 10 of 17 results)

  • Articles and reports: 12-001-X201100111444
    Description:

    Data linkage is the act of bringing together records that are believed to belong to the same unit (e.g., person or business) from two or more files. It is a very common way to enhance dimensions such as time and breadth or depth of detail. Data linkage is often not an error-free process and can lead to linking a pair of records that do not belong to the same unit. There is an explosion of record linkage applications, yet there has been little work on assuring the quality of analyses using such linked files. Naively treating such a linked file as if it were linked without errors will, in general, lead to biased estimates. This paper develops a maximum likelihood estimator for contingency tables and logistic regression with incorrectly linked records. The estimation technique is simple and is implemented using the well-known EM algorithm. A well known method of linking records in the present context is probabilistic data linking. The paper demonstrates the effectiveness of the proposed estimators in an empirical study which uses probabilistic data linkage.

    Release date: 2011-06-29

  • Articles and reports: 11-522-X200800010975
    Description:

    A major issue in official statistics is the availability of objective measures supporting the based-on-fact decision process. Istat has developed an Information System to assess survey quality. Among other standard quality indicators, nonresponse rates are systematically computed and stored for all surveys. Such a rich information base permits analysis over time and comparisons among surveys. The paper focuses on the analysis of interrelationships between data collection mode and other survey characteristics on total nonresponse. Particular attention is devoted to the extent to which multi-mode data collection improves response rates.

    Release date: 2009-12-03

  • Articles and reports: 11-522-X200800011003
    Description:

    This study examined the feasibility of developing correction factors to adjust self-reported measures of Body Mass Index to more closely approximate measured values. Data are from the 2005 Canadian Community Health Survey where respondents were asked to report their height and weight and were subsequently measured. Regression analyses were used to determine which socio-demographic and health characteristics were associated with the discrepancies between reported and measured values. The sample was then split into two groups. In the first, the self-reported BMI and the predictors of the discrepancies were regressed on the measured BMI. Correction equations were generated using all predictor variables that were significant at the p<0.05 level. These correction equations were then tested in the second group to derive estimates of sensitivity, specificity and of obesity prevalence. Logistic regression was used to examine the relationship between measured, reported and corrected BMI and obesity-related health conditions. Corrected estimates provided more accurate measures of obesity prevalence, mean BMI and sensitivity levels. Self-reported data exaggerated the relationship between BMI and health conditions, while in most cases the corrected estimates provided odds ratios that were more similar to those generated with the measured BMI.

    Release date: 2009-12-03

  • Articles and reports: 11-522-X20050019473
    Description:

    This talk will provide a brief overview of some of some techniques, highlighting the advantages and disadvantages of each, with particular reference to the data types usually encountered in the social sciences. The overview will touch on naïve methods based on the use of latent variable scores, and on methods for correcting and / or avoiding the biases associated with such analyses. The talk will conclude with a brief description of some recent applications to probit and logistic regression with latent predictor variables, and with suggestions for future research.

    Release date: 2007-03-02

  • Articles and reports: 11-522-X20030017595
    Geography: Canada
    Description:

    This paper discusses challenges faced in locating recent immigrants and implementing strategies to increase response rates for the Longitudinal Survey of Immigrants to Canada (LSIC). It also presents a model-assisted technique for adjusting for non-response, based on the approach proposed by Eltinge-Yanseneh to define adjustment classes.

    Release date: 2005-01-26

  • Articles and reports: 11-522-X20030017598
    Description:

    This paper looks at descriptive statistics to evaluate non-response in the Labour Force Survey (LFS) and also at ways of improving the current methodology of making non-response adjustments.

    Release date: 2005-01-26

  • Articles and reports: 12-001-X20030026777
    Description:

    The Accuracy and Coverage Evaluation survey was conducted to estimate the coverage in the 2000 U.S. Census. After field procedures were completed, several types of missing data had to be addressed to apply dual-system estimation. Some housing units were not interviewed. Two noninterview adjustments were devised from the same set of interviews, one for each of two points in time. In addition, the resident, match, or enumeration status of some respondents was not determined. Methods applied in the past were replaced to accommodate a tighter schedule to compute and verify the estimates. This paper presents the extent of missing data in the survey, describes the procedures applied, comparing them to past and current alternatives, and provides analytical summaries of the procedures, including comparisons of dual-system estimates of population under alternatives. Because the resulting levels of missing data were low, it appears that alternative procedures would not have affected the results substantially. However some changes in the estimates are noted.

    Release date: 2004-01-27

  • Articles and reports: 12-001-X20010026097
    Description:

    A compositional time series is defined as a multivariate time series in which each of the series has values bounded between zero and one and the sum of the series equals one at each time point. Data with such characteristics are observed in repeated surveys when a survey variable has a multinomial response but interest lies in the proportion of units classified in each of its categories. In this case, the survey estimates are proportions of a whole subject to a unity-sum constraint. In this paper we employ a state space approach for modelling compositional time series from repeated surveys taking into account the sampling errors. The additive logistic transformation is used in order to guarantee predictions and signal estimates bounded between zero and one which satisfy the unity-sum constraint. The method is applied to compositional data from the Brazilian Labour Force Survey. Estimates of the vector of proportions and the unemployment rate are obtained. In addition, the structural components of the signal vector, such as the seasonals and the trends, are produced.

    Release date: 2002-02-28

  • Articles and reports: 12-001-X20010015858
    Description:

    The objective of this paper is to study and measure the change (from the initial to the final weight) which results from the procedure used to modify weights. A breakdown of the final weights is proposed in order to evaluate the relative impact of the nonresponse adjustment, the correction for poststratification and the interaction between these two adjustments. This measure of change is used as a tool for comparing the effectiveness of the various methods for adjusting for nonresponse, in particular the methods relying on the formation of Response Homogeneity Groups. The measure of change is examined through a simulation study, which uses data from a Statistics Canada longitudinal survey, the Survey of Labour and Income Dynamics. The measure of change is also applied to data obtained from a second longitudinal survey, the National Longitudinal Survey of Children and Youth.

    Release date: 2001-08-22

  • Articles and reports: 81-003-X19990045143
    Geography: Canada
    Description:

    This article explores regional differences among students who drop out of Canadian universities and community colleges.

    Release date: 2000-09-01
Reference (1)

Reference (1) ((1 result))

  • Surveys and statistical programs – Documentation: 11-522-X19980015036
    Description:

    Multivariate logistic regression, introduced by Glonek and McCullagh (1995) as a generalisation of logistic regression, is useful in the analysis of longitudinal data as it allows for dependent repeated observations of a categorical variable and for incomplete response profiles. We show how the method can be extended to deal with data from complex surveys and we illustrate it on data from the Swiss Labour Force Survey. The effect of the sampling weights on the parameter estimates and their standard errors is considered.

    Release date: 1999-10-22
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