Statistical techniques
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All (9) ((9 results))
- Articles and reports: 11-522-X202100100017Description: The outbreak of the COVID-19 pandemic required the Government of Canada to provide relevant and timely information to support decision-making around a host of issues, including personal protective equipment (PPE) procurement and deployment. Our team built a compartmental epidemiological model from an existing code base to project PPE demand under a range of epidemiological scenarios. This model was further enhanced using data science techniques, which allowed for the rapid development and dissemination of model results to inform policy decisions.
Key Words: COVID-19; SARS-CoV-2; Epidemiological model; Data science; Personal Protective Equipment (PPE); SEIR
Release date: 2021-10-22 - Articles and reports: 12-001-X202100100004Description:
Multiple data sources are becoming increasingly available for statistical analyses in the era of big data. As an important example in finite-population inference, we consider an imputation approach to combining data from a probability survey and big found data. We focus on the case when the study variable is observed in the big data only, but the other auxiliary variables are commonly observed in both data. Unlike the usual imputation for missing data analysis, we create imputed values for all units in the probability sample. Such mass imputation is attractive in the context of survey data integration (Kim and Rao, 2012). We extend mass imputation as a tool for data integration of survey data and big non-survey data. The mass imputation methods and their statistical properties are presented. The matching estimator of Rivers (2007) is also covered as a special case. Variance estimation with mass-imputed data is discussed. The simulation results demonstrate the proposed estimators outperform existing competitors in terms of robustness and efficiency.
Release date: 2021-06-24 - Articles and reports: 11-633-X2017009Description:
This document describes the procedures for using linked administrative data sources to estimate paid parental leave rates in Canada and the issues surrounding this use.
Release date: 2017-08-29 - Articles and reports: 12-001-X201600114540Description:
In this paper, we compare the EBLUP and pseudo-EBLUP estimators for small area estimation under the nested error regression model and three area level model-based estimators using the Fay-Herriot model. We conduct a design-based simulation study to compare the model-based estimators for unit level and area level models under informative and non-informative sampling. In particular, we are interested in the confidence interval coverage rate of the unit level and area level estimators. We also compare the estimators if the model has been misspecified. Our simulation results show that estimators based on the unit level model perform better than those based on the area level. The pseudo-EBLUP estimator is the best among unit level and area level estimators.
Release date: 2016-06-22 - 5. Theoretical and empirical properties of model assisted decision-based regression estimators ArchivedArticles and reports: 12-001-X201400114004Description:
In 2009, two major surveys in the Governments Division of the U.S. Census Bureau were redesigned to reduce sample size, save resources, and improve the precision of the estimates (Cheng, Corcoran, Barth and Hogue 2009). The new design divides each of the traditional state by government-type strata with sufficiently many units into two sub-strata according to each governmental unit’s total payroll, in order to sample less from the sub-stratum with small size units. The model-assisted approach is adopted in estimating population totals. Regression estimators using auxiliary variables are obtained either within each created sub-stratum or within the original stratum by collapsing two sub-strata. A decision-based method was proposed in Cheng, Slud and Hogue (2010), applying a hypothesis test to decide which regression estimator is used within each original stratum. Consistency and asymptotic normality of these model-assisted estimators are established here, under a design-based or model-assisted asymptotic framework. Our asymptotic results also suggest two types of consistent variance estimators, one obtained by substituting unknown quantities in the asymptotic variances and the other by applying the bootstrap. The performance of all the estimators of totals and of their variance estimators are examined in some empirical studies. The U.S. Annual Survey of Public Employment and Payroll (ASPEP) is used to motivate and illustrate our study.
Release date: 2014-06-27 - 6. Historical Data Linkage of Tax Records on Labour and Income: The Case of the Living in Canada Survey Pilot ArchivedArticles and reports: 89-648-X2013002Geography: CanadaDescription:
Data matching is a common practice used to reduce the response burden of respondents and to improve the quality of the information collected from respondents when the linkage method does not introduce bias. However, historical linkage, which consists in linking external records from previous years to the year of the initial wave of a survey, is relatively rare and, until now, had not been used at Statistics Canada. The present paper describes the method used to link the records from the Living in Canada Survey pilot to historical tax data on income and labour (T1 and T4 files). It presents the evolution of the linkage rate going back over time and compares earnings data collected from personal income tax returns with those collected from employers file. To illustrate the new possibilities of analysis offered by this type of linkage, the study concludes with an earnings profile by age and sex for different cohorts based on year of birth.
Release date: 2013-01-24 - Articles and reports: 11-522-X200600110402Description:
This paper explains how to append census area-level summary data to survey or administrative data. It uses examples from survey datasets present in Statistics Canada Research Data Centres, but the methods also apply to external datasets, including administrative datasets. Four examples illustrate common situations faced by researchers: (1) when the survey (or administrative) and census data both contain the same level of geographic identifiers, coded to the same year standard ("vintage") of census geography (for example, if both have 2001 DA); (2) when the two files contain geographic identifiers of the same vintage, but at different levels of census geography (for example, 1996 EA in the survey, but 1996 CT in the census data); (3) when the two files contain data coded to different vintages of census geography (such as 1996 EA for the survey, but 2001 DA for the census); (4) when the survey data are lacking in geographic identifiers, and those identifiers must first be generated from postal codes present on the file. The examples are shown using SAS syntax, but the principles apply to other programming languages or statistical packages.
Release date: 2008-03-17 - 8. Merging area-level census data with survey data in Statistics Canada research data centres ArchivedArticles and reports: 12-002-X20060019254Description:
This article explains how to append census area-level summary data to survey or administrative data. It uses examples from datasets present in Statistics Canada Research Data Centres, but the methods also apply to external datasets. Four examples illustrate common situations faced by researchers: (1) when the survey (or administrative) and census data both contain the same level of geographic identifiers, coded to the same year standard ("vintage") of census geography; (2) when the two files contain geographic identifiers of the same vintage, but at different levels of census geography; (3) when the two files contain data coded to different vintages of census geography; (4) when the survey data are lacking in geographic identifiers, and those identifiers must first be generated from postal codes present on the file. The examples are shown using SAS syntax, but the principles apply to other programming languages or statistical packages.
Release date: 2006-07-18 - 9. Project on Matching Census 1986 Database and Manitoba Health Care Files: Private Households Component ArchivedArticles and reports: 11F0019M1996091Geography: Province or territoryDescription:
Introduction: In the current economic context, all partners in health care delivery systems, be they public or private, are obliged to identify the factors that influence the utilization of health care services. To improve our understanding of the phenomena that underlie these relationships, Statistics Canada and the Manitoba Centre for Health Policy and Evaluation have just set up a new database. For a representative sample of the population of the province of Manitoba, cross-sectional microdata on individuals' health and socio-economic characteristics were linked with detailed longitudinal data on utilization of health care services.
Data and methods: The 1986-87 Health and Activity Limitation Survey, the 1986 Census and the files of Manitoba Health were matched (without using names or addresses) by means of the CANLINK software. In the pilot project, 20,000 units were selected from the Census according to modern sampling techniques. Before the files were matched, consultations were held and an agreement was signed by all parties in order to establish a framework for protecting privacy and preserving the confidentiality of the data.
Results: A matching rate of 74% was obtained for private households. A quality evaluation based on the comparisons of names and addresses over a small subsample established that the overall concordance rate among matched pairs was 95.5%. The match rates and concordance rates varied according to age and household composition. Estimates produced from the sample accurately reflected the socio-demographic profile, mortality, hospitalization rate, health care costs and consumption of health care by Manitoba residents.
Discussion: The matching rate of 74% was satisfactory in comparison with the response rates reported in most population surveys. Because of the excellent concordance rate and the accuracy of the estimates obtained from the sample, this database will provide an adequate basis for studying the association between socio-demographic characteristics, health and health care utilization in province of Manitoba.
Release date: 1996-03-30
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Analysis (9)
Analysis (9) ((9 results))
- Articles and reports: 11-522-X202100100017Description: The outbreak of the COVID-19 pandemic required the Government of Canada to provide relevant and timely information to support decision-making around a host of issues, including personal protective equipment (PPE) procurement and deployment. Our team built a compartmental epidemiological model from an existing code base to project PPE demand under a range of epidemiological scenarios. This model was further enhanced using data science techniques, which allowed for the rapid development and dissemination of model results to inform policy decisions.
Key Words: COVID-19; SARS-CoV-2; Epidemiological model; Data science; Personal Protective Equipment (PPE); SEIR
Release date: 2021-10-22 - Articles and reports: 12-001-X202100100004Description:
Multiple data sources are becoming increasingly available for statistical analyses in the era of big data. As an important example in finite-population inference, we consider an imputation approach to combining data from a probability survey and big found data. We focus on the case when the study variable is observed in the big data only, but the other auxiliary variables are commonly observed in both data. Unlike the usual imputation for missing data analysis, we create imputed values for all units in the probability sample. Such mass imputation is attractive in the context of survey data integration (Kim and Rao, 2012). We extend mass imputation as a tool for data integration of survey data and big non-survey data. The mass imputation methods and their statistical properties are presented. The matching estimator of Rivers (2007) is also covered as a special case. Variance estimation with mass-imputed data is discussed. The simulation results demonstrate the proposed estimators outperform existing competitors in terms of robustness and efficiency.
Release date: 2021-06-24 - Articles and reports: 11-633-X2017009Description:
This document describes the procedures for using linked administrative data sources to estimate paid parental leave rates in Canada and the issues surrounding this use.
Release date: 2017-08-29 - Articles and reports: 12-001-X201600114540Description:
In this paper, we compare the EBLUP and pseudo-EBLUP estimators for small area estimation under the nested error regression model and three area level model-based estimators using the Fay-Herriot model. We conduct a design-based simulation study to compare the model-based estimators for unit level and area level models under informative and non-informative sampling. In particular, we are interested in the confidence interval coverage rate of the unit level and area level estimators. We also compare the estimators if the model has been misspecified. Our simulation results show that estimators based on the unit level model perform better than those based on the area level. The pseudo-EBLUP estimator is the best among unit level and area level estimators.
Release date: 2016-06-22 - 5. Theoretical and empirical properties of model assisted decision-based regression estimators ArchivedArticles and reports: 12-001-X201400114004Description:
In 2009, two major surveys in the Governments Division of the U.S. Census Bureau were redesigned to reduce sample size, save resources, and improve the precision of the estimates (Cheng, Corcoran, Barth and Hogue 2009). The new design divides each of the traditional state by government-type strata with sufficiently many units into two sub-strata according to each governmental unit’s total payroll, in order to sample less from the sub-stratum with small size units. The model-assisted approach is adopted in estimating population totals. Regression estimators using auxiliary variables are obtained either within each created sub-stratum or within the original stratum by collapsing two sub-strata. A decision-based method was proposed in Cheng, Slud and Hogue (2010), applying a hypothesis test to decide which regression estimator is used within each original stratum. Consistency and asymptotic normality of these model-assisted estimators are established here, under a design-based or model-assisted asymptotic framework. Our asymptotic results also suggest two types of consistent variance estimators, one obtained by substituting unknown quantities in the asymptotic variances and the other by applying the bootstrap. The performance of all the estimators of totals and of their variance estimators are examined in some empirical studies. The U.S. Annual Survey of Public Employment and Payroll (ASPEP) is used to motivate and illustrate our study.
Release date: 2014-06-27 - 6. Historical Data Linkage of Tax Records on Labour and Income: The Case of the Living in Canada Survey Pilot ArchivedArticles and reports: 89-648-X2013002Geography: CanadaDescription:
Data matching is a common practice used to reduce the response burden of respondents and to improve the quality of the information collected from respondents when the linkage method does not introduce bias. However, historical linkage, which consists in linking external records from previous years to the year of the initial wave of a survey, is relatively rare and, until now, had not been used at Statistics Canada. The present paper describes the method used to link the records from the Living in Canada Survey pilot to historical tax data on income and labour (T1 and T4 files). It presents the evolution of the linkage rate going back over time and compares earnings data collected from personal income tax returns with those collected from employers file. To illustrate the new possibilities of analysis offered by this type of linkage, the study concludes with an earnings profile by age and sex for different cohorts based on year of birth.
Release date: 2013-01-24 - Articles and reports: 11-522-X200600110402Description:
This paper explains how to append census area-level summary data to survey or administrative data. It uses examples from survey datasets present in Statistics Canada Research Data Centres, but the methods also apply to external datasets, including administrative datasets. Four examples illustrate common situations faced by researchers: (1) when the survey (or administrative) and census data both contain the same level of geographic identifiers, coded to the same year standard ("vintage") of census geography (for example, if both have 2001 DA); (2) when the two files contain geographic identifiers of the same vintage, but at different levels of census geography (for example, 1996 EA in the survey, but 1996 CT in the census data); (3) when the two files contain data coded to different vintages of census geography (such as 1996 EA for the survey, but 2001 DA for the census); (4) when the survey data are lacking in geographic identifiers, and those identifiers must first be generated from postal codes present on the file. The examples are shown using SAS syntax, but the principles apply to other programming languages or statistical packages.
Release date: 2008-03-17 - 8. Merging area-level census data with survey data in Statistics Canada research data centres ArchivedArticles and reports: 12-002-X20060019254Description:
This article explains how to append census area-level summary data to survey or administrative data. It uses examples from datasets present in Statistics Canada Research Data Centres, but the methods also apply to external datasets. Four examples illustrate common situations faced by researchers: (1) when the survey (or administrative) and census data both contain the same level of geographic identifiers, coded to the same year standard ("vintage") of census geography; (2) when the two files contain geographic identifiers of the same vintage, but at different levels of census geography; (3) when the two files contain data coded to different vintages of census geography; (4) when the survey data are lacking in geographic identifiers, and those identifiers must first be generated from postal codes present on the file. The examples are shown using SAS syntax, but the principles apply to other programming languages or statistical packages.
Release date: 2006-07-18 - 9. Project on Matching Census 1986 Database and Manitoba Health Care Files: Private Households Component ArchivedArticles and reports: 11F0019M1996091Geography: Province or territoryDescription:
Introduction: In the current economic context, all partners in health care delivery systems, be they public or private, are obliged to identify the factors that influence the utilization of health care services. To improve our understanding of the phenomena that underlie these relationships, Statistics Canada and the Manitoba Centre for Health Policy and Evaluation have just set up a new database. For a representative sample of the population of the province of Manitoba, cross-sectional microdata on individuals' health and socio-economic characteristics were linked with detailed longitudinal data on utilization of health care services.
Data and methods: The 1986-87 Health and Activity Limitation Survey, the 1986 Census and the files of Manitoba Health were matched (without using names or addresses) by means of the CANLINK software. In the pilot project, 20,000 units were selected from the Census according to modern sampling techniques. Before the files were matched, consultations were held and an agreement was signed by all parties in order to establish a framework for protecting privacy and preserving the confidentiality of the data.
Results: A matching rate of 74% was obtained for private households. A quality evaluation based on the comparisons of names and addresses over a small subsample established that the overall concordance rate among matched pairs was 95.5%. The match rates and concordance rates varied according to age and household composition. Estimates produced from the sample accurately reflected the socio-demographic profile, mortality, hospitalization rate, health care costs and consumption of health care by Manitoba residents.
Discussion: The matching rate of 74% was satisfactory in comparison with the response rates reported in most population surveys. Because of the excellent concordance rate and the accuracy of the estimates obtained from the sample, this database will provide an adequate basis for studying the association between socio-demographic characteristics, health and health care utilization in province of Manitoba.
Release date: 1996-03-30
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