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This document presents the geographical distribution of federal government expenditures and staff for the fiscal year 2004/2005.

We discuss methods for the analysis of case-control studies in which the controls are drawn using a complex sample survey. The most straightforward method is the standard survey approach based on weighted versions of population estimating equations. We also look at more efficient methods and compare their robustness to model mis-specification in simple cases. Case-control family studies, where the within-cluster structure is of interest in its own right, are also discussed briefly.

Calibration weighting can be used to adjust for unit nonresponse and/or coverage errors under appropriate quasi-randomization models. Alternative calibration adjustments that are asymptotically identical in a purely sampling context can diverge when used in this manner. Introducing instrumental variables into calibration weighting makes it possible for nonresponse (say) to be a function of a set of characteristics other than those in the calibration vector. When the calibration adjustment has a nonlinear form, a variant of the jackknife can remove the need for iteration in variance estimation.

The theory of multiple imputation for missing data requires that imputations be made conditional on the sampling design. However, most standard software packages for performing model-based multiple imputation assume simple random samples, leading many practitioners not to account for complex sample design features, such as stratification and clustering, in their imputations. Theory predicts that analyses of such multiply-imputed data sets can yield biased estimates from the design-based perspective. In this article, we illustrate through simulation that (i) the bias can be severe when the design features are related to the survey variables of interest, and (ii) the bias can be reduced by controlling for the design features in the imputation models. The simulations also illustrate that conditioning on irrelevant design features in the imputation models can yield conservative inferences, provided that the models include other relevant predictors. These results suggest a prescription for imputers: the safest course of action is to include design variables in the specification of imputation models. Using real data, we demonstrate a simple approach for incorporating complex design features that can be used with some of the standard software packages for creating multiple imputations.

In this article, we propose a Bernoulli-type bootstrap method that can easily handle multi-stage stratified designs where sampling fractions are large, provided simple random sampling without replacement is used at each stage. The method provides a set of replicate weights which yield consistent variance estimates for both smooth and non-smooth estimators. The method's strength is in its simplicity. It can easily be extended to any number of stages without much complication. The main idea is to either keep or replace a sampling unit at each stage with preassigned probabilities, to construct the bootstrap sample. A limited simulation study is presented to evaluate performance and, as an illustration, we apply the method to the 1997 Japanese National Survey of Prices.

In this paper, the geometric, optimization-based, and Lavallée and Hidiroglou (LH) approaches to stratification are compared. The geometric stratification method is an approximation, whereas the other two approaches, which employ numerical methods to perform stratification, may be seen as optimal stratification methods. The algorithm of the geometric stratification is very simple compared to the two other approaches, but it does not take into account the construction of a take-all stratum, which is usually constructed when a positively skewed population is stratified. In the optimization-based stratification, one may consider any form of optimization function and its constraints. In a comparative numerical study based on five positively skewed artificial populations, the optimization approach was more efficient in each of the cases studied compared to the geometric stratification. In addition, the geometric and optimization approaches are compared with the LH algorithm. In this comparison, the geometric stratification approach was found to be less efficient than the LH algorithm, whereas efficiency of the optimization approach was similar to the efficiency of the LH algorithm. Nevertheless, strata boundaries evaluated via the geometric stratification may be seen as efficient starting points for the optimization approach.

To select a survey sample, it happens that one does not have a frame containing the desired collection units, but rather another frame of units linked in a certain way to the list of collection units. It can then be considered to select a sample from the available frame in order to produce an estimate for the desired target population by using the links existing between the two. This can be designated by Indirect Sampling.

Estimation for the target population surveyed by Indirect Sampling can constitute a big challenge, in particular if the links between the units of the two are not one-to-one. The problem comes especially from the difficulty to associate a selection probability, or an estimation weight, to the surveyed units of the target population. In order to solve this type of estimation problem, the Generalized Weight Share Method (GWSM) has been developed by Lavallée (1995) and Lavallée (2002). The GWSM provides an estimation weight for every surveyed unit of the target population.

This paper first describes Indirect Sampling, which constitutes the foundations of the GWSM. Second, an overview of the GWSM is given where we formulate the GWSM in a theoretical framework using matrix notation. Third, we present some properties of the GWSM such as unbiasedness and transitivity. Fourth, we consider the special case where the links between the two populations are expressed by indicator variables. Fifth, some special typical linkages are studied to assess their impact on the GWSM. Finally, we consider the problem of optimality. We obtain optimal weights in a weak sense (for specific values of the variable of interest), and conditions for which these weights are also optimal in a strong sense and independent of the variable of interest.

A survey of tourist visits originating intra and extra-region in Brittany was needed. For concrete material reasons, "border surveys" could no longer be used. The major problem is the lack of a sampling frame that allows for direct contact with tourists. This problem was addressed by applying the indirect sampling method, the weighting for which is obtained using the generalized weight share method developed recently by Lavallée (1995), Lavallée (2002), Deville (1999) and also presented recently in Lavallée and Caron (2001). This article shows how to adapt the method to the survey. A number of extensions are required. One of the extensions, designed to estimate the total of a population from which a Bernouilli sample has been taken, will be developed.

Félix-Medina and Thompson (2004) proposed a variant of Link-tracing sampling in which it is assumed that a portion of the population, not necessarily the major portion, is covered by a frame of disjoint sites where members of the population can be found with high probabilities. A sample of sites is selected and the people in each of the selected sites are asked to nominate other members of the population. They proposed maximum likelihood estimators of the population sizes which perform acceptably provided that for each site the probability that a member is nominated by that site, called the nomination probability, is not small. In this research we consider Félix-Medina and Thompson's variant and propose three sets of estimators of the population sizes derived under the Bayesian approach. Two of the sets of estimators were obtained using improper prior distributions of the population sizes, and the other using Poisson prior distributions. However, we use the Bayesian approach only to assist us in the construction of estimators, while inferences about the population sizes are made under the frequentist approach. We propose two types of partly design-based variance estimators and confidence intervals. One of them is obtained using a bootstrap and the other using the delta method along with the assumption of asymptotic normality. The results of a simulation study indicate that (i) when the nomination probabilities are not small each of the proposed sets of estimators performs well and very similarly to maximum likelihood estimators; (ii) when the nomination probabilities are small the set of estimators derived using Poisson prior distributions still performs acceptably and does not have the problems of bias that maximum likelihood estimators have, and (iii) the previous results do not depend on the size of the fraction of the population covered by the frame.

Survey sampling to estimate a Consumer Price Index (CPI) is quite complicated, generally requiring a combination of data from at least two surveys: one giving prices, one giving expenditure weights. Fundamentally different approaches to the sampling process - probability sampling and purposive sampling - have each been strongly advocated and are used by different countries in the collection of price data. By constructing a small "world" of purchases and prices from scanner data on cereal and then simulating various sampling and estimation techniques, we compare the results of two design and estimation approaches: the probability approach of the United States and the purposive approach of the United Kingdom. For the same amount of information collected, but given the use of different estimators, the United Kingdom's methods appear to offer better overall accuracy in targeting a population superlative consumer price index.

This publication presents detailed statistical tables, graphs and documentation supporting the public sector employment and finance data released in The Daily.

This publication contains population estimates by age and sex for Canada, provinces, territories, census divisions, census metropolitan areas and economic regions. It also includes, for provinces and territories, estimates by age, sex and marital status as well as estimates for census families.

The estimates are based on the 2001 Census results, which have been adjusted for net census undercoverage. The publication also includes statistics for the demographic components that were used to produce the population estimates (births, deaths, marriages, divorces, immigration, emigration, net temporary emigration, returning emigration, internal migration and non-permanent residents) by age and sex. In addition, the publication contains highlights of current demographic trends and a description of the methodology.

The print version of the publication includes a CD-ROM that provides additional data such as a chronological series of estimates by various levels of geography. With regard to provinces and territories, the estimates date back to 1971 (tables and animated age pyramid), 1986 for census divisions, census metropolitan areas and economic regions as well as census families.

The time series available on the CD-ROM can be easily captured and manipulated by analysts who want to create customized demographic analyses in any spreadsheet program. The population figures can be used, for example, to calculate per-capita rates required for market research, quantitative analysis and planning.

These tables provide information on the television viewing habits of Canadians. The tabulations focus on the average hours per week of television viewing, the type of program and the Canadian content, as well as the signal source of the station. Data are available by demographic characteristics of survey respondents and by province. Additionally, the data in these tables can add to the understanding of the recreation patterns and time use of Canadians.

This comprehensive source on international service transactions contains aggregate and detailed breakouts by type of service each year since 1989. Major categories are travel, transportation, commercial and government services. Commercial services, comprising a range of business and professional services are categorized by geographical area (United States, European Union and all other countries), industry, country of control (Canada, United States, other) and whether or not the service was with foreign affiliated companies; these details are presented from 1996.

New with the 1999 issue are annual breakdowns from 1991 of total services for 8 additional countries beyond the 47 already published. Each country is broken down into the following categories: travel, transportation, commercial and government services. For Canada as a whole, quarterly data for these same categories and 19 subcategories are also published from 1997, on both a raw and seasonally adjusted basis. The publication includes several pages of data analysis accompanied by graphics, definitions and data quality measures. Statistics are derived from surveys, administrative data and other sources.

This publication describes the evolution of the Canadian business environment in light of economic changes in Canada from 1991 to 2001. The publication shows business and employment dynamics in Canada during this period. It provides (1) statistics that show the direct impact of these changes on business creation (firm births) and business destruction (firm deaths); (2) the relative share and distribution of businesses and employment across various categories of firms (Size - small, medium and large size firms, Industry - low-knowledge, medium-knowledge and high-knowledge industries, as well as goods and services industries and by Geography-Province); and (3) it examines survival rates of newly created businesses (lifespan of new businesses).

In 2004, as part of its General Social Survey program, Statistics Canada conducted a survey on victimization and public perceptions of crime and the justice system. It was the fourth time that the General Social Survey (GSS) had examined victimization - previous surveys were conducted in 1988, 1993, and 1999. The target population was Canadians aged 15 years and older living in the ten provinces.

This survey also included a test collection of telephone survey data in the Northwest Territories, Nunavut and Yukon. This document contains data tables for these territories produced from the sample of this test collection.

This document presents the geographical distribution of federal government expenditures and staff for the fiscal year 2004/2005.

We discuss methods for the analysis of case-control studies in which the controls are drawn using a complex sample survey. The most straightforward method is the standard survey approach based on weighted versions of population estimating equations. We also look at more efficient methods and compare their robustness to model mis-specification in simple cases. Case-control family studies, where the within-cluster structure is of interest in its own right, are also discussed briefly.

Calibration weighting can be used to adjust for unit nonresponse and/or coverage errors under appropriate quasi-randomization models. Alternative calibration adjustments that are asymptotically identical in a purely sampling context can diverge when used in this manner. Introducing instrumental variables into calibration weighting makes it possible for nonresponse (say) to be a function of a set of characteristics other than those in the calibration vector. When the calibration adjustment has a nonlinear form, a variant of the jackknife can remove the need for iteration in variance estimation.

The theory of multiple imputation for missing data requires that imputations be made conditional on the sampling design. However, most standard software packages for performing model-based multiple imputation assume simple random samples, leading many practitioners not to account for complex sample design features, such as stratification and clustering, in their imputations. Theory predicts that analyses of such multiply-imputed data sets can yield biased estimates from the design-based perspective. In this article, we illustrate through simulation that (i) the bias can be severe when the design features are related to the survey variables of interest, and (ii) the bias can be reduced by controlling for the design features in the imputation models. The simulations also illustrate that conditioning on irrelevant design features in the imputation models can yield conservative inferences, provided that the models include other relevant predictors. These results suggest a prescription for imputers: the safest course of action is to include design variables in the specification of imputation models. Using real data, we demonstrate a simple approach for incorporating complex design features that can be used with some of the standard software packages for creating multiple imputations.

In this article, we propose a Bernoulli-type bootstrap method that can easily handle multi-stage stratified designs where sampling fractions are large, provided simple random sampling without replacement is used at each stage. The method provides a set of replicate weights which yield consistent variance estimates for both smooth and non-smooth estimators. The method's strength is in its simplicity. It can easily be extended to any number of stages without much complication. The main idea is to either keep or replace a sampling unit at each stage with preassigned probabilities, to construct the bootstrap sample. A limited simulation study is presented to evaluate performance and, as an illustration, we apply the method to the 1997 Japanese National Survey of Prices.

In this paper, the geometric, optimization-based, and Lavallée and Hidiroglou (LH) approaches to stratification are compared. The geometric stratification method is an approximation, whereas the other two approaches, which employ numerical methods to perform stratification, may be seen as optimal stratification methods. The algorithm of the geometric stratification is very simple compared to the two other approaches, but it does not take into account the construction of a take-all stratum, which is usually constructed when a positively skewed population is stratified. In the optimization-based stratification, one may consider any form of optimization function and its constraints. In a comparative numerical study based on five positively skewed artificial populations, the optimization approach was more efficient in each of the cases studied compared to the geometric stratification. In addition, the geometric and optimization approaches are compared with the LH algorithm. In this comparison, the geometric stratification approach was found to be less efficient than the LH algorithm, whereas efficiency of the optimization approach was similar to the efficiency of the LH algorithm. Nevertheless, strata boundaries evaluated via the geometric stratification may be seen as efficient starting points for the optimization approach.

To select a survey sample, it happens that one does not have a frame containing the desired collection units, but rather another frame of units linked in a certain way to the list of collection units. It can then be considered to select a sample from the available frame in order to produce an estimate for the desired target population by using the links existing between the two. This can be designated by Indirect Sampling.

Estimation for the target population surveyed by Indirect Sampling can constitute a big challenge, in particular if the links between the units of the two are not one-to-one. The problem comes especially from the difficulty to associate a selection probability, or an estimation weight, to the surveyed units of the target population. In order to solve this type of estimation problem, the Generalized Weight Share Method (GWSM) has been developed by Lavallée (1995) and Lavallée (2002). The GWSM provides an estimation weight for every surveyed unit of the target population.

This paper first describes Indirect Sampling, which constitutes the foundations of the GWSM. Second, an overview of the GWSM is given where we formulate the GWSM in a theoretical framework using matrix notation. Third, we present some properties of the GWSM such as unbiasedness and transitivity. Fourth, we consider the special case where the links between the two populations are expressed by indicator variables. Fifth, some special typical linkages are studied to assess their impact on the GWSM. Finally, we consider the problem of optimality. We obtain optimal weights in a weak sense (for specific values of the variable of interest), and conditions for which these weights are also optimal in a strong sense and independent of the variable of interest.

A survey of tourist visits originating intra and extra-region in Brittany was needed. For concrete material reasons, "border surveys" could no longer be used. The major problem is the lack of a sampling frame that allows for direct contact with tourists. This problem was addressed by applying the indirect sampling method, the weighting for which is obtained using the generalized weight share method developed recently by Lavallée (1995), Lavallée (2002), Deville (1999) and also presented recently in Lavallée and Caron (2001). This article shows how to adapt the method to the survey. A number of extensions are required. One of the extensions, designed to estimate the total of a population from which a Bernouilli sample has been taken, will be developed.

Félix-Medina and Thompson (2004) proposed a variant of Link-tracing sampling in which it is assumed that a portion of the population, not necessarily the major portion, is covered by a frame of disjoint sites where members of the population can be found with high probabilities. A sample of sites is selected and the people in each of the selected sites are asked to nominate other members of the population. They proposed maximum likelihood estimators of the population sizes which perform acceptably provided that for each site the probability that a member is nominated by that site, called the nomination probability, is not small. In this research we consider Félix-Medina and Thompson's variant and propose three sets of estimators of the population sizes derived under the Bayesian approach. Two of the sets of estimators were obtained using improper prior distributions of the population sizes, and the other using Poisson prior distributions. However, we use the Bayesian approach only to assist us in the construction of estimators, while inferences about the population sizes are made under the frequentist approach. We propose two types of partly design-based variance estimators and confidence intervals. One of them is obtained using a bootstrap and the other using the delta method along with the assumption of asymptotic normality. The results of a simulation study indicate that (i) when the nomination probabilities are not small each of the proposed sets of estimators performs well and very similarly to maximum likelihood estimators; (ii) when the nomination probabilities are small the set of estimators derived using Poisson prior distributions still performs acceptably and does not have the problems of bias that maximum likelihood estimators have, and (iii) the previous results do not depend on the size of the fraction of the population covered by the frame.

Survey sampling to estimate a Consumer Price Index (CPI) is quite complicated, generally requiring a combination of data from at least two surveys: one giving prices, one giving expenditure weights. Fundamentally different approaches to the sampling process - probability sampling and purposive sampling - have each been strongly advocated and are used by different countries in the collection of price data. By constructing a small "world" of purchases and prices from scanner data on cereal and then simulating various sampling and estimation techniques, we compare the results of two design and estimation approaches: the probability approach of the United States and the purposive approach of the United Kingdom. For the same amount of information collected, but given the use of different estimators, the United Kingdom's methods appear to offer better overall accuracy in targeting a population superlative consumer price index.

This guide presents information of interest to users of data from the Survey of Household Spending, which gathers information on the spending habits, dwelling characteristics and household equipment of Canadian households. The survey covers private households in the 10 provinces. (The territories are surveyed every second year, starting in 1999.)

This guide includes definitions of survey terms and variables, as well as descriptions of survey methodology and data quality. One section describes the various statistics that can be created using expenditure data (e.g., budget share, market share, aggregates and medians).

Statistics Canada's approach to gathering and disseminating economic data has developed over several decades into a highly integrated system for collection and estimation that feeds the framework of the Canadian System of National Accounts.

The key to this approach was creation of the Unified Enterprise Survey, the goal of which was to improve the consistency, coherence, breadth and depth of business survey data.

The UES did so by bringing many of Statistics Canada's individual annual business surveys under a common framework. This framework included a single survey frame, a sample design framework, conceptual harmonization of survey content, means of using relevant administrative data, common data collection, processing and analysis tools, and a common data warehouse.

The General Social Survey (GSS) is an annual survey that monitors changes and emerging trends in Canadian Society. For the fourth time in Canada, the GSS has collected national level time use data. The GSS is funded through a government initiative aimed to fill data gaps for policy research. In this paper we present the policy framework that supports the survey, and discuss the impact of that framework on the content decisions that GSS has made. Following a brief review of the major findings from the first three cycles of time use data we discuss the lessons learned and best practices in the development, collection and processing of these data in Canada. Finally, we compare the methods and content of the Canadian time use survey with the US survey.

This series presents detailed analyses based on the 2005 General Social Survey on Time Use data. Each report covers a specific subject developed from detailed information on the daily activities of Canadians. Links to other products related to time use are also available.

This paper provides a brief description of the methodology currently used to produce the annual volume of hours worked consistent with the System of National Accounts (SNA). These data are used for labour input in the annual and quarterly measures of labour productivity, as well as in the annual measures of multifactor productivity. For this purpose, hours worked are broken down by educational level and age group, so that changes in the composition of the labour force can be taken into account. They are also used to calculate hourly compensation and the unit labour cost and for simulations of the SNA Input-Output Model; as such, they are integrated as labour force inputs into most SNA satellite accounts (i.e., environment, tourism).

The Standard Geographical Classification (SGC) is a system of names and codes representing areas of Canada. It consists of a three-tiered hierarchy - province or territory, census division, and census subdivision. This relationship is reflected in the seven-digit code. The SGC is used to identify information for particular geographical areas and to tabulate statistics. This volume is designed as a reference and coding manual. It contains tables of SGC units with their names and codes, as well as tables of metropolitan areas. This preliminary version of Volume I will be followed in January 2007 by the final version.

The National, Census Divisions and Census Subdivisions Reference Maps reference guide is available for the following products: Census Division and Census Subdivision Reference Maps, by Province or Territory, 2006 Census and four national maps. The national maps of Canada at a 1:7,500,000 scale showing census divisions, point locations of census metropolitan areas and census agglomerations, statistical area classification and economic regions and census divisions. The Reference Guide describes the content and applications of these products, as well as data quality, and other information.

The Preview of Products and Services offers a complete overview of the proposed products and services that will be released based on the 2006 Census of Population and 2006 Census of Agriculture results. Information (where applicable) will include major characteristics and content, "What's new?" in comparison to 2001, levels of geography, availability/delivery methods, release timeframe and pricing.

The preview is now exclusively an Internet product for 2006 and is no longer available in a formalized print format (i.e. newsletter publication); however, "print-friendly" format is available via the Internet. This product will be updated periodically as details regarding products and services become finalized.

This paper examines the revision cycle for labour productivity estimates over the period 2001 to 2004.

The User Guide to Record Linkage Feedback Reports C1 and C2 is intended for the users of the reports. The reports were developed to facilitate the exchange of information and decisions between the Canadian Cancer Registry and the Provincial and Territorial Cancer Registries.