Data analysis
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All (6) ((6 results))
- Articles and reports: 12-001-X201700254872Description:
This note discusses the theoretical foundations for the extension of the Wilson two-sided coverage interval to an estimated proportion computed from complex survey data. The interval is shown to be asymptotically equivalent to an interval derived from a logistic transformation. A mildly better version is discussed, but users may prefer constructing a one-sided interval already in the literature.
Release date: 2017-12-21 - Articles and reports: 12-001-X201700254887Description:
This paper proposes a new approach to decompose the wage difference between men and women that is based on a calibration procedure. This approach generalizes two current decomposition methods that are re-expressed using survey weights. The first one is the Blinder-Oaxaca method and the second one is a reweighting method proposed by DiNardo, Fortin and Lemieux. The new approach provides a weighting system that enables us to estimate such parameters of interest like quantiles. An application to data from the Swiss Structure of Earnings Survey shows the interest of this method.
Release date: 2017-12-21 - Articles and reports: 12-001-X201700114820Description:
Measurement errors can induce bias in the estimation of transitions, leading to erroneous conclusions about labour market dynamics. Traditional literature on gross flows estimation is based on the assumption that measurement errors are uncorrelated over time. This assumption is not realistic in many contexts, because of survey design and data collection strategies. In this work, we use a model-based approach to correct observed gross flows from classification errors with latent class Markov models. We refer to data collected with the Italian Continuous Labour Force Survey, which is cross-sectional, quarterly, with a 2-2-2 rotating design. The questionnaire allows us to use multiple indicators of labour force conditions for each quarter: two collected in the first interview, and a third collected one year later. Our approach provides a method to estimate labour market mobility, taking into account correlated errors and the rotating design of the survey. The best-fitting model is a mixed latent class Markov model with covariates affecting latent transitions and correlated errors among indicators; the mixture components are of mover-stayer type. The better fit of the mixture specification is due to more accurately estimated latent transitions.
Release date: 2017-06-22 - Articles and reports: 12-001-X201700114822Description:
We use a Bayesian method to infer about a finite population proportion when binary data are collected using a two-fold sample design from small areas. The two-fold sample design has a two-stage cluster sample design within each area. A former hierarchical Bayesian model assumes that for each area the first stage binary responses are independent Bernoulli distributions, and the probabilities have beta distributions which are parameterized by a mean and a correlation coefficient. The means vary with areas but the correlation is the same over areas. However, to gain some flexibility we have now extended this model to accommodate different correlations. The means and the correlations have independent beta distributions. We call the former model a homogeneous model and the new model a heterogeneous model. All hyperparameters have proper noninformative priors. An additional complexity is that some of the parameters are weakly identified making it difficult to use a standard Gibbs sampler for computation. So we have used unimodal constraints for the beta prior distributions and a blocked Gibbs sampler to perform the computation. We have compared the heterogeneous and homogeneous models using an illustrative example and simulation study. As expected, the two-fold model with heterogeneous correlations is preferred.
Release date: 2017-06-22 - Articles and reports: 18-001-X2017002Description:
This working paper presents a methodology to measure remoteness at the community level. The method takes into account some of the recent literature on the subject, as well as new computational opportunities provided by the integration of official statistics with data from non-official statistical sources. The approach that was used in the computations accounts for multiple points of access to services; it also establishes a continuum between communities with different transportation infrastructures and connectivity while at the same time retaining the information on the community transportation infrastructures in the database. In addition, a method to implement accessibility measures to selected services is also outlined and a sample of accessibility measures are computed.
Release date: 2017-05-09 - Articles and reports: 11-633-X2017006Description:
This paper describes a method of imputing missing postal codes in a longitudinal database. The 1991 Canadian Census Health and Environment Cohort (CanCHEC), which contains information on individuals from the 1991 Census long-form questionnaire linked with T1 tax return files for the 1984-to-2011 period, is used to illustrate and validate the method. The cohort contains up to 28 consecutive fields for postal code of residence, but because of frequent gaps in postal code history, missing postal codes must be imputed. To validate the imputation method, two experiments were devised where 5% and 10% of all postal codes from a subset with full history were randomly removed and imputed.
Release date: 2017-03-13
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Analysis (6)
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- Articles and reports: 12-001-X201700254872Description:
This note discusses the theoretical foundations for the extension of the Wilson two-sided coverage interval to an estimated proportion computed from complex survey data. The interval is shown to be asymptotically equivalent to an interval derived from a logistic transformation. A mildly better version is discussed, but users may prefer constructing a one-sided interval already in the literature.
Release date: 2017-12-21 - Articles and reports: 12-001-X201700254887Description:
This paper proposes a new approach to decompose the wage difference between men and women that is based on a calibration procedure. This approach generalizes two current decomposition methods that are re-expressed using survey weights. The first one is the Blinder-Oaxaca method and the second one is a reweighting method proposed by DiNardo, Fortin and Lemieux. The new approach provides a weighting system that enables us to estimate such parameters of interest like quantiles. An application to data from the Swiss Structure of Earnings Survey shows the interest of this method.
Release date: 2017-12-21 - Articles and reports: 12-001-X201700114820Description:
Measurement errors can induce bias in the estimation of transitions, leading to erroneous conclusions about labour market dynamics. Traditional literature on gross flows estimation is based on the assumption that measurement errors are uncorrelated over time. This assumption is not realistic in many contexts, because of survey design and data collection strategies. In this work, we use a model-based approach to correct observed gross flows from classification errors with latent class Markov models. We refer to data collected with the Italian Continuous Labour Force Survey, which is cross-sectional, quarterly, with a 2-2-2 rotating design. The questionnaire allows us to use multiple indicators of labour force conditions for each quarter: two collected in the first interview, and a third collected one year later. Our approach provides a method to estimate labour market mobility, taking into account correlated errors and the rotating design of the survey. The best-fitting model is a mixed latent class Markov model with covariates affecting latent transitions and correlated errors among indicators; the mixture components are of mover-stayer type. The better fit of the mixture specification is due to more accurately estimated latent transitions.
Release date: 2017-06-22 - Articles and reports: 12-001-X201700114822Description:
We use a Bayesian method to infer about a finite population proportion when binary data are collected using a two-fold sample design from small areas. The two-fold sample design has a two-stage cluster sample design within each area. A former hierarchical Bayesian model assumes that for each area the first stage binary responses are independent Bernoulli distributions, and the probabilities have beta distributions which are parameterized by a mean and a correlation coefficient. The means vary with areas but the correlation is the same over areas. However, to gain some flexibility we have now extended this model to accommodate different correlations. The means and the correlations have independent beta distributions. We call the former model a homogeneous model and the new model a heterogeneous model. All hyperparameters have proper noninformative priors. An additional complexity is that some of the parameters are weakly identified making it difficult to use a standard Gibbs sampler for computation. So we have used unimodal constraints for the beta prior distributions and a blocked Gibbs sampler to perform the computation. We have compared the heterogeneous and homogeneous models using an illustrative example and simulation study. As expected, the two-fold model with heterogeneous correlations is preferred.
Release date: 2017-06-22 - Articles and reports: 18-001-X2017002Description:
This working paper presents a methodology to measure remoteness at the community level. The method takes into account some of the recent literature on the subject, as well as new computational opportunities provided by the integration of official statistics with data from non-official statistical sources. The approach that was used in the computations accounts for multiple points of access to services; it also establishes a continuum between communities with different transportation infrastructures and connectivity while at the same time retaining the information on the community transportation infrastructures in the database. In addition, a method to implement accessibility measures to selected services is also outlined and a sample of accessibility measures are computed.
Release date: 2017-05-09 - Articles and reports: 11-633-X2017006Description:
This paper describes a method of imputing missing postal codes in a longitudinal database. The 1991 Canadian Census Health and Environment Cohort (CanCHEC), which contains information on individuals from the 1991 Census long-form questionnaire linked with T1 tax return files for the 1984-to-2011 period, is used to illustrate and validate the method. The cohort contains up to 28 consecutive fields for postal code of residence, but because of frequent gaps in postal code history, missing postal codes must be imputed. To validate the imputation method, two experiments were devised where 5% and 10% of all postal codes from a subset with full history were randomly removed and imputed.
Release date: 2017-03-13
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