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All (18) (0 to 10 of 18 results)
- Articles and reports: 75F0002M2024002Description: This discussion paper describes considerations for applying the Market Basket Measure (MBM) methodology onto a purely administrative data source. The paper will begin by outlining a rationale for estimating MBM poverty statistics using administrative income data sources. It then explains a proposal for creating annual samples along with the caveats of creating these samples, followed by a brief analysis using the proposed samples. The paper concludes with potential future improvements to the samples and provides the opportunity for reader’s feedback.Release date: 2024-02-08
- Articles and reports: 11-633-X2024001Description: The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 35 years.Release date: 2024-01-22
- Articles and reports: 12-001-X202300200001Description: When a Medicare healthcare provider is suspected of billing abuse, a population of payments X made to that provider over a fixed timeframe is isolated. A certified medical reviewer, in a time-consuming process, can determine the overpayment Y = X - (amount justified by the evidence) associated with each payment. Typically, there are too many payments in the population to examine each with care, so a probability sample is selected. The sample overpayments are then used to calculate a 90% lower confidence bound for the total population overpayment. This bound is the amount demanded for recovery from the provider. Unfortunately, classical methods for calculating this bound sometimes fail to provide the 90% confidence level, especially when using a stratified sample. In this paper, 166 redacted samples from Medicare integrity investigations are displayed and described, along with 156 associated payment populations. The 7,588 examined (Y, X) sample pairs show (1) Medicare audits have high error rates: more than 76% of these payments were considered to have been paid in error; and (2) the patterns in these samples support an “All-or-Nothing” mixture model for (Y, X) previously defined in the literature. Model-based Monte Carlo testing procedures for Medicare sampling plans are discussed, as well as stratification methods based on anticipated model moments. In terms of viability (achieving the 90% confidence level) a new stratification method defined here is competitive with the best of the many existing methods tested and seems less sensitive to choice of operating parameters. In terms of overpayment recovery (equivalent to precision) the new method is also comparable to the best of the many existing methods tested. Unfortunately, no stratification algorithm tested was ever viable for more than about half of the 104 test populations.Release date: 2024-01-03
- Articles and reports: 12-001-X202300200006Description: Survey researchers are increasingly turning to multimode data collection to deal with declines in survey response rates and increasing costs. An efficient approach offers the less costly modes (e.g., web) followed with a more expensive mode for a subsample of the units (e.g., households) within each primary sampling unit (PSU). We present two alternatives to this traditional design. One alternative subsamples PSUs rather than units to constrain costs. The second is a hybrid design that includes a clustered (two-stage) sample and an independent, unclustered sample. Using a simulation, we demonstrate the hybrid design has considerable advantages.Release date: 2024-01-03
- Articles and reports: 12-001-X202300200009Description: In this paper, we investigate how a big non-probability database can be used to improve estimates of finite population totals from a small probability sample through data integration techniques. In the situation where the study variable is observed in both data sources, Kim and Tam (2021) proposed two design-consistent estimators that can be justified through dual frame survey theory. First, we provide conditions ensuring that these estimators are more efficient than the Horvitz-Thompson estimator when the probability sample is selected using either Poisson sampling or simple random sampling without replacement. Then, we study the class of QR predictors, introduced by Särndal and Wright (1984), to handle the less common case where the non-probability database contains no study variable but auxiliary variables. We also require that the non-probability database is large and can be linked to the probability sample. We provide conditions ensuring that the QR predictor is asymptotically design-unbiased. We derive its asymptotic design variance and provide a consistent design-based variance estimator. We compare the design properties of different predictors, in the class of QR predictors, through a simulation study. This class includes a model-based predictor, a model-assisted estimator and a cosmetic estimator. In our simulation setups, the cosmetic estimator performed slightly better than the model-assisted estimator. These findings are confirmed by an application to La Poste data, which also illustrates that the properties of the cosmetic estimator are preserved irrespective of the observed non-probability sample.Release date: 2024-01-03
- Articles and reports: 12-001-X202300200014Description: Many things have been written about Jean-Claude Deville in tributes from the statistical community (see Tillé, 2022a; Tillé, 2022b; Christine, 2022; Ardilly, 2022; and Matei, 2022) and from the École nationale de la statistique et de l’administration économique (ENSAE) and the Société française de statistique. Pascal Ardilly, David Haziza, Pierre Lavallée and Yves Tillé provide an in-depth look at Jean-Claude Deville’s contributions to survey theory. To pay tribute to him, I would like to discuss Jean-Claude Deville’s contribution to the more day-to-day application of methodology for all the statisticians at the Institut national de la statistique et des études économiques (INSEE) and at the public statistics service. To do this, I will use my work experience, and particularly the four years (1992 to 1996) I spent working with him in the Statistical Methods Unit and the discussions we had thereafter, especially in the 2000s on the rolling census.Release date: 2024-01-03
- Articles and reports: 75F0002M2022003Description: This discussion paper describes the proposed methodology for a Northern Market Basket Measure (MBM-N) for Nunavut, as well as identifies research which could be conducted in preparation for the 2023 review. The paper presents initial MBM-N thresholds and provides preliminary poverty estimates for reference years 2018 to 2021. A review period will follow the release of this paper, during which time Statistics Canada and Employment and Social Development Canada will welcome feedback from interested parties and work with experts, stakeholders, indigenous organizations, federal, provincial and territorial officials to validate the results.Release date: 2023-06-21
- Articles and reports: 12-001-X202200200010Description:
Multilevel time series (MTS) models are applied to estimate trends in time series of antenatal care coverage at several administrative levels in Bangladesh, based on repeated editions of the Bangladesh Demographic and Health Survey (BDHS) within the period 1994-2014. MTS models are expressed in an hierarchical Bayesian framework and fitted using Markov Chain Monte Carlo simulations. The models account for varying time lags of three or four years between the editions of the BDHS and provide predictions for the intervening years as well. It is proposed to apply cross-sectional Fay-Herriot models to the survey years separately at district level, which is the most detailed regional level. Time series of these small domain predictions at the district level and their variance-covariance matrices are used as input series for the MTS models. Spatial correlations among districts, random intercept and slope at the district level, and different trend models at district level and higher regional levels are examined in the MTS models to borrow strength over time and space. Trend estimates at district level are obtained directly from the model outputs, while trend estimates at higher regional and national levels are obtained by aggregation of the district level predictions, resulting in a numerically consistent set of trend estimates.
Release date: 2022-12-15 - Articles and reports: 12-001-X202200200012Description:
In many applications, the population means of geographically adjacent small areas exhibit a spatial variation. If available auxiliary variables do not adequately account for the spatial pattern, the residual variation will be included in the random effects. As a result, the independent and identical distribution assumption on random effects of the Fay-Herriot model will fail. Furthermore, limited resources often prevent numerous sub-populations from being included in the sample, resulting in non-sampled small areas. The problem can be exacerbated for predicting means of non-sampled small areas using the above Fay-Herriot model as the predictions will be made based solely on the auxiliary variables. To address such inadequacy, we consider Bayesian spatial random-effect models that can accommodate multiple non-sampled areas. Under mild conditions, we establish the propriety of the posterior distributions for various spatial models for a useful class of improper prior densities on model parameters. The effectiveness of these spatial models is assessed based on simulated and real data. Specifically, we examine predictions of statewide four-person family median incomes based on the 1990 Current Population Survey and the 1980 Census for the United States of America.
Release date: 2022-12-15 - Articles and reports: 11-633-X2022007Description:
This paper investigates how Statistics Canada can increase trust by giving users the ability to authenticate data from its website through digital signatures and blockchain technology.
Release date: 2022-09-19
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Articles and reports (18)
Articles and reports (18) (0 to 10 of 18 results)
- Articles and reports: 75F0002M2024002Description: This discussion paper describes considerations for applying the Market Basket Measure (MBM) methodology onto a purely administrative data source. The paper will begin by outlining a rationale for estimating MBM poverty statistics using administrative income data sources. It then explains a proposal for creating annual samples along with the caveats of creating these samples, followed by a brief analysis using the proposed samples. The paper concludes with potential future improvements to the samples and provides the opportunity for reader’s feedback.Release date: 2024-02-08
- Articles and reports: 11-633-X2024001Description: The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 35 years.Release date: 2024-01-22
- Articles and reports: 12-001-X202300200001Description: When a Medicare healthcare provider is suspected of billing abuse, a population of payments X made to that provider over a fixed timeframe is isolated. A certified medical reviewer, in a time-consuming process, can determine the overpayment Y = X - (amount justified by the evidence) associated with each payment. Typically, there are too many payments in the population to examine each with care, so a probability sample is selected. The sample overpayments are then used to calculate a 90% lower confidence bound for the total population overpayment. This bound is the amount demanded for recovery from the provider. Unfortunately, classical methods for calculating this bound sometimes fail to provide the 90% confidence level, especially when using a stratified sample. In this paper, 166 redacted samples from Medicare integrity investigations are displayed and described, along with 156 associated payment populations. The 7,588 examined (Y, X) sample pairs show (1) Medicare audits have high error rates: more than 76% of these payments were considered to have been paid in error; and (2) the patterns in these samples support an “All-or-Nothing” mixture model for (Y, X) previously defined in the literature. Model-based Monte Carlo testing procedures for Medicare sampling plans are discussed, as well as stratification methods based on anticipated model moments. In terms of viability (achieving the 90% confidence level) a new stratification method defined here is competitive with the best of the many existing methods tested and seems less sensitive to choice of operating parameters. In terms of overpayment recovery (equivalent to precision) the new method is also comparable to the best of the many existing methods tested. Unfortunately, no stratification algorithm tested was ever viable for more than about half of the 104 test populations.Release date: 2024-01-03
- Articles and reports: 12-001-X202300200006Description: Survey researchers are increasingly turning to multimode data collection to deal with declines in survey response rates and increasing costs. An efficient approach offers the less costly modes (e.g., web) followed with a more expensive mode for a subsample of the units (e.g., households) within each primary sampling unit (PSU). We present two alternatives to this traditional design. One alternative subsamples PSUs rather than units to constrain costs. The second is a hybrid design that includes a clustered (two-stage) sample and an independent, unclustered sample. Using a simulation, we demonstrate the hybrid design has considerable advantages.Release date: 2024-01-03
- Articles and reports: 12-001-X202300200009Description: In this paper, we investigate how a big non-probability database can be used to improve estimates of finite population totals from a small probability sample through data integration techniques. In the situation where the study variable is observed in both data sources, Kim and Tam (2021) proposed two design-consistent estimators that can be justified through dual frame survey theory. First, we provide conditions ensuring that these estimators are more efficient than the Horvitz-Thompson estimator when the probability sample is selected using either Poisson sampling or simple random sampling without replacement. Then, we study the class of QR predictors, introduced by Särndal and Wright (1984), to handle the less common case where the non-probability database contains no study variable but auxiliary variables. We also require that the non-probability database is large and can be linked to the probability sample. We provide conditions ensuring that the QR predictor is asymptotically design-unbiased. We derive its asymptotic design variance and provide a consistent design-based variance estimator. We compare the design properties of different predictors, in the class of QR predictors, through a simulation study. This class includes a model-based predictor, a model-assisted estimator and a cosmetic estimator. In our simulation setups, the cosmetic estimator performed slightly better than the model-assisted estimator. These findings are confirmed by an application to La Poste data, which also illustrates that the properties of the cosmetic estimator are preserved irrespective of the observed non-probability sample.Release date: 2024-01-03
- Articles and reports: 12-001-X202300200014Description: Many things have been written about Jean-Claude Deville in tributes from the statistical community (see Tillé, 2022a; Tillé, 2022b; Christine, 2022; Ardilly, 2022; and Matei, 2022) and from the École nationale de la statistique et de l’administration économique (ENSAE) and the Société française de statistique. Pascal Ardilly, David Haziza, Pierre Lavallée and Yves Tillé provide an in-depth look at Jean-Claude Deville’s contributions to survey theory. To pay tribute to him, I would like to discuss Jean-Claude Deville’s contribution to the more day-to-day application of methodology for all the statisticians at the Institut national de la statistique et des études économiques (INSEE) and at the public statistics service. To do this, I will use my work experience, and particularly the four years (1992 to 1996) I spent working with him in the Statistical Methods Unit and the discussions we had thereafter, especially in the 2000s on the rolling census.Release date: 2024-01-03
- Articles and reports: 75F0002M2022003Description: This discussion paper describes the proposed methodology for a Northern Market Basket Measure (MBM-N) for Nunavut, as well as identifies research which could be conducted in preparation for the 2023 review. The paper presents initial MBM-N thresholds and provides preliminary poverty estimates for reference years 2018 to 2021. A review period will follow the release of this paper, during which time Statistics Canada and Employment and Social Development Canada will welcome feedback from interested parties and work with experts, stakeholders, indigenous organizations, federal, provincial and territorial officials to validate the results.Release date: 2023-06-21
- Articles and reports: 12-001-X202200200010Description:
Multilevel time series (MTS) models are applied to estimate trends in time series of antenatal care coverage at several administrative levels in Bangladesh, based on repeated editions of the Bangladesh Demographic and Health Survey (BDHS) within the period 1994-2014. MTS models are expressed in an hierarchical Bayesian framework and fitted using Markov Chain Monte Carlo simulations. The models account for varying time lags of three or four years between the editions of the BDHS and provide predictions for the intervening years as well. It is proposed to apply cross-sectional Fay-Herriot models to the survey years separately at district level, which is the most detailed regional level. Time series of these small domain predictions at the district level and their variance-covariance matrices are used as input series for the MTS models. Spatial correlations among districts, random intercept and slope at the district level, and different trend models at district level and higher regional levels are examined in the MTS models to borrow strength over time and space. Trend estimates at district level are obtained directly from the model outputs, while trend estimates at higher regional and national levels are obtained by aggregation of the district level predictions, resulting in a numerically consistent set of trend estimates.
Release date: 2022-12-15 - Articles and reports: 12-001-X202200200012Description:
In many applications, the population means of geographically adjacent small areas exhibit a spatial variation. If available auxiliary variables do not adequately account for the spatial pattern, the residual variation will be included in the random effects. As a result, the independent and identical distribution assumption on random effects of the Fay-Herriot model will fail. Furthermore, limited resources often prevent numerous sub-populations from being included in the sample, resulting in non-sampled small areas. The problem can be exacerbated for predicting means of non-sampled small areas using the above Fay-Herriot model as the predictions will be made based solely on the auxiliary variables. To address such inadequacy, we consider Bayesian spatial random-effect models that can accommodate multiple non-sampled areas. Under mild conditions, we establish the propriety of the posterior distributions for various spatial models for a useful class of improper prior densities on model parameters. The effectiveness of these spatial models is assessed based on simulated and real data. Specifically, we examine predictions of statewide four-person family median incomes based on the 1990 Current Population Survey and the 1980 Census for the United States of America.
Release date: 2022-12-15 - Articles and reports: 11-633-X2022007Description:
This paper investigates how Statistics Canada can increase trust by giving users the ability to authenticate data from its website through digital signatures and blockchain technology.
Release date: 2022-09-19
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