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41. The use of estimating equations to perform a calibration on complex parameters Archived
Articles and reports: 12-001-X201100111451
Description:
In the calibration method proposed by Deville and Särndal (1992), the calibration equations take only exact estimates of auxiliary variable totals into account. This article examines other parameters besides totals for calibration. Parameters that are considered complex include the ratio, median or variance of auxiliary variables.
Release date: 2011-06-29
42. Bayesian penalized spline model-based inference for finite population proportion in unequal probability sampling Archived
Articles and reports: 12-001-X201000111250
Description:
We propose a Bayesian Penalized Spline Predictive (BPSP) estimator for a finite population proportion in an unequal probability sampling setting. This new method allows the probabilities of inclusion to be directly incorporated into the estimation of a population proportion, using a probit regression of the binary outcome on the penalized spline of the inclusion probabilities. The posterior predictive distribution of the population proportion is obtained using Gibbs sampling. The advantages of the BPSP estimator over the Hájek (HK), Generalized Regression (GR), and parametric model-based prediction estimators are demonstrated by simulation studies and a real example in tax auditing. Simulation studies show that the BPSP estimator is more efficient, and its 95% credible interval provides better confidence coverage with shorter average width than the HK and GR estimators, especially when the population proportion is close to zero or one or when the sample is small. Compared to linear model-based predictive estimators, the BPSP estimators are robust to model misspecification and influential observations in the sample.
Release date: 2010-06-29
43. Pseudo empirical likelihood inference for multiple surveys and multiple-frame surveys Archived
Articles and reports: 11-536-X200900110806
Description:
Recent work using a pseudo empirical likelihood (EL) method for finite population inferences with complex survey data focused primarily on a single survey sample, non-stratified or stratified, with considerable effort devoted to computational procedures. In this talk we present a pseudo empirical likelihood approach to inference from multiple surveys and multiple-frame surveys, two commonly encountered problems in survey practice. We show that inferences about the common parameter of interest and the effective use of various types of auxiliary information can be conveniently carried out through the constrained maximization of joint pseudo EL function. We obtain asymptotic results which are used for constructing the pseudo EL ratio confidence intervals, either using a chi-square approximation or a bootstrap calibration. All related computational problems can be handled using existing algorithms on stratified sampling after suitable re-formulation.
Release date: 2009-08-11
44. A Bayesian allocation of undecided voters Archived
Articles and reports: 12-001-X200800110606
Description:
Data from election polls in the US are typically presented in two-way categorical tables, and there are many polls before the actual election in November. For example, in the Buckeye State Poll in 1998 for governor there are three polls, January, April and October; the first category represents the candidates (e.g., Fisher, Taft and other) and the second category represents the current status of the voters (likely to vote and not likely to vote for governor of Ohio). There is a substantial number of undecided voters for one or both categories in all three polls, and we use a Bayesian method to allocate the undecided voters to the three candidates. This method permits modeling different patterns of missingness under ignorable and nonignorable assumptions, and a multinomial-Dirichlet model is used to estimate the cell probabilities which can help to predict the winner. We propose a time-dependent nonignorable nonresponse model for the three tables. Here, a nonignorable nonresponse model is centered on an ignorable nonresponse model to induce some flexibility and uncertainty about ignorabilty or nonignorability. As competitors we also consider two other models, an ignorable and a nonignorable nonresponse model. These latter two models assume a common stochastic process to borrow strength over time. Markov chain Monte Carlo methods are used to fit the models. We also construct a parameter that can potentially be used to predict the winner among the candidates in the November election.
Release date: 2008-06-26
45. Robust Bayesian predictive inference for the finite population quantile of a small area Archived
Articles and reports: 11-522-X200600110392
Description:
We use a robust Bayesian method to analyze data with possibly nonignorable nonresponse and selection bias. A robust logistic regression model is used to relate the response indicators (Bernoulli random variable) to the covariates, which are available for everyone in the finite population. This relationship can adequately explain the difference between respondents and nonrespondents for the sample. This robust model is obtained by expanding the standard logistic regression model to a mixture of Student's distributions, thereby providing propensity scores (selection probability) which are used to construct adjustment cells. The nonrespondents' values are filled in by drawing a random sample from a kernel density estimator, formed from the respondents' values within the adjustment cells. Prediction uses a linear spline rank-based regression of the response variable on the covariates by areas, sampling the errors from another kernel density estimator; thereby further robustifying our method. We use Markov chain Monte Carlo (MCMC) methods to fit our model. The posterior distribution of a quantile of the response variable is obtained within each sub-area using the order statistic over all the individuals (sampled and nonsampled). We compare our robust method with recent parametric methods
Release date: 2008-03-17
46. Flexible models for analyzing longitudinal data in population health Archived
Articles and reports: 11-522-X200600110398
Description:
The study of longitudinal data is vital in terms of accurately observing changes in responses of interest for individuals, communities, and larger populations over time. Linear mixed effects models (for continuous responses observed over time) and generalized linear mixed effects models and generalized estimating equations (for more general responses such as binary or count data observed over time) are the most popular techniques used for analyzing longitudinal data from health studies, though, as with all modeling techniques, these approaches have limitations, partly due to their underlying assumptions. In this review paper, we will discuss some advances, including curve-based techniques, which make modeling longitudinal data more flexible. Three examples will be presented from the health literature utilizing these more flexible procedures, with the goal of demonstrating that some otherwise difficult questions can be reasonably answered when analyzing complex longitudinal data in population health studies.
Release date: 2008-03-17
47. Causal inference in observational studies using health administrative data Archived
Articles and reports: 11-522-X200600110419
Description:
Health services research generally relies on observational data to compare outcomes of patients receiving different therapies. Comparisons of patient groups in observational studies may be biased, in that outcomes differ due to both the effects of treatment and the effects of patient prognosis. In some cases, especially when data are collected on detailed clinical risk factors, these differences can be controlled for using statistical or epidemiological methods. In other cases, when unmeasured characteristics of the patient population affect both the decision to provide therapy and the outcome, these differences cannot be removed using standard techniques. Use of health administrative data requires particular cautions in undertaking observational studies since important clinical information does not exist. We discuss several statistical and epidemiological approaches to remove overt (measurable) and hidden (unmeasurable) bias in observational studies. These include regression model-based case-mix adjustment, propensity-based matching, redefining the exposure variable of interest, and the econometric technique of instrumental variable (IV) analysis. These methods are illustrated using examples from the medical literature including prediction of one-year mortality following heart attack; the return to health care spending in higher spending U.S. regions in terms of clinical and financial benefits; and the long-term survival benefits of invasive cardiac management of heart attack patients. It is possible to use health administrative data for observational studies provided careful attention is paid to addressing issues of reverse causation and unmeasured confounding.
Release date: 2008-03-17
48. Defining and Measuring Metropolitan Areas: A Comparison Between Canada and the United States Archived
Articles and reports: 92F0138M2008002
Description:
On November 26 2006, the Organization for Economic Co-operation and Development (OECD) held an international workshop on defining and measuring metropolitan regions. The reasons the OECD organized this workshop are listed below.
1. Metropolitan Regions have become a crucial economic actor in today's highly integrated world. Not only do they play their traditional role of growth poles in their countries but they function as essential nodes of the global economy.2. Policy makers, international organisations and research networks are increasingly called to compare the economic and social performances of Metropolitan Regions across countries. Examples of this work undertaken in international organisation and networks include the UN-Habitat, the EU Urban Audit, ESPON and the OECD Competitive Cities.3. The scope of what we can learn from these international comparisons, however, is limited by the lack of a comparable definition of Metropolitan Regions. Although most countries have their own definitions, these vary significantly from one country to another. Furthermore, in search for higher cross-country comparability, international initiatives have - somehow paradoxically - generated an even larger number of definitions.4. In principle, there is no clear reason to prefer one definition to another. As each definition has been elaborated for a specific analytical purpose, it captures some features of a Metropolitan Region while it tends to overlook others. The issue, rather, is that we do not know the pros and the cons of different definitions nor, most important, the analytical implications of using one definition rather than another. 5. In order to respond to these questions, the OECD hosted an international workshop on 'Defining and Measuring Metropolitan Regions'. The workshop brought together major international organisations (the UN, Eurostat, the World Bank, and the OECD), National Statistical Offices and researchers from this field. The aim of the workshop was to develop some 'guiding principles', which could be agreed upon among the participants and would eventually provide the basis for some form of 'International Guidance' for comparing Metropolitan Regions across countries.
This working paper was presented at this workshop. It provides the conceptual and methodological basis for the definition of metropolitan areas in Canada and provides a detailed comparison of Canada's methodology to that of the USA. The intent was to encourage discussion regarding Canada's approach to defining metropolitan areas in the effort to identify the 'guiding principles'. It is being made available as a working paper to continue this discussion and to provide background to the user community to encourage dialogue and commentary from the user community regarding Canada's metropolitan area methodology.
Release date: 2008-02-20
49. How Postal Codes Map to Geographic Areas Archived
Articles and reports: 92F0138M2007001
Description:
Statistics Canada creates files that provide the link between postal codes and the geographic areas by which it disseminates statistical data. By linking postal codes to the Statistics Canada geographic areas, Statistics Canada facilitates the extraction and subsequent aggregation of data for selected geographic areas from files available to users. Users can then take data from Statistics Canada for their areas and tabulate this with other data for these same areas to create a combined statistical profile for these areas.
An issue has been the methodology used by Statistics Canada to establish the linkage of postal codes to geographic areas. In order to address this issue, Statistics Canada decided to create a conceptual framework on which to base the rules for linking postal codes and Statistics Canada's geographic areas. This working paper presents the conceptual framework and the geocoding rules. The methodology described in this paper will be the basis for linking postal codes to the 2006 Census geographic areas. This paper is presented for feedback from users of Statistics Canada's postal codes related products.
Release date: 2007-02-12
50. A nonresponse model approach to inference under imputation for missing survey data Archived
Articles and reports: 12-001-X20060019257
Description:
In the presence of item nonreponse, two approaches have been traditionally used to make inference on parameters of interest. The first approach assumes uniform response within imputation cells whereas the second approach assumes ignorable response but make use of a model on the variable of interest as the basis for inference. In this paper, we propose a third appoach that assumes a specified ignorable response mechanism without having to specify a model on the variable of interest. In this case, we show how to obtain imputed values which lead to estimators of a total that are approximately unbiased under the proposed approach as well as the second approach. Variance estimators of the imputed estimators that are approximately unbiased are also obtained using an approach of Fay (1991) in which the order of sampling and response is reversed. Finally, simulation studies are conducted to investigate the finite sample performance of the methods in terms of bias and mean square error.
Release date: 2006-07-20

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Analysis (92)

Analysis (92) (20 to 30 of 92 results)

21. Bayesian predictive inference of a proportion under a two-fold small area model with heterogeneous correlations Archived
Articles and reports: 12-001-X201700114822
Description:
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
22. A note on the concept of invariance in two-phase sampling designs Archived
Articles and reports: 12-001-X201600214662
Description:
Two-phase sampling designs are often used in surveys when the sampling frame contains little or no auxiliary information. In this note, we shed some light on the concept of invariance, which is often mentioned in the context of two-phase sampling designs. We define two types of invariant two-phase designs: strongly invariant and weakly invariant two-phase designs. Some examples are given. Finally, we describe the implications of strong and weak invariance from an inference point of view.
Release date: 2016-12-20
23. A short note on quantile and expectile estimation in unequal probability samples Archived
Articles and reports: 12-001-X201600114545
Description:
The estimation of quantiles is an important topic not only in the regression framework, but also in sampling theory. A natural alternative or addition to quantiles are expectiles. Expectiles as a generalization of the mean have become popular during the last years as they not only give a more detailed picture of the data than the ordinary mean, but also can serve as a basis to calculate quantiles by using their close relationship. We show, how to estimate expectiles under sampling with unequal probabilities and how expectiles can be used to estimate the distribution function. The resulting fitted distribution function estimator can be inverted leading to quantile estimates. We run a simulation study to investigate and compare the efficiency of the expectile based estimator.
Release date: 2016-06-22
24. Methodological Challenges in Official Statistics Archived
Articles and reports: 11-522-X201700014704
Description:
We identify several research areas and topics for methodological research in official statistics. We argue why these are important, and why these are the most important ones for official statistics. We describe the main topics in these research areas and sketch what seems to be the most promising ways to address them. Here we focus on: (i) Quality of National accounts, in particular the rate of growth of GNI (ii) Big data, in particular how to create representative estimates and how to make the most of big data when this is difficult or impossible. We also touch upon: (i) Increasing timeliness of preliminary and final statistical estimates (ii) Statistical analysis, in particular of complex and coherent phenomena. These topics are elements in the present Strategic Methodological Research Program that has recently been adopted at Statistics Netherlands
Release date: 2016-03-24
25. Big Data: A Survey Research Perspective Archived
Articles and reports: 11-522-X201700014713
Description:
Big data is a term that means different things to different people. To some, it means datasets so large that our traditional processing and analytic systems can no longer accommodate them. To others, it simply means taking advantage of existing datasets of all sizes and finding ways to merge them with the goal of generating new insights. The former view poses a number of important challenges to traditional market, opinion, and social research. In either case, there are implications for the future of surveys that are only beginning to be explored.
Release date: 2016-03-24
26. Towards a Quality Framework for Blends of Designed and Organic Data Archived
Articles and reports: 11-522-X201700014727
Description:
"Probability samples of near-universal frames of households and persons, administered standardized measures, yielding long multivariate data records, and analyzed with statistical procedures reflecting the design – these have been the cornerstones of the empirical social sciences for 75 years. That measurement structure have given the developed world almost all of what we know about our societies and their economies. The stored survey data form a unique historical record. We live now in a different data world than that in which the leadership of statistical agencies and the social sciences were raised. High-dimensional data are ubiquitously being produced from Internet search activities, mobile Internet devices, social media, sensors, retail store scanners, and other devices. Some estimate that these data sources are increasing in size at the rate of 40% per year. Together their sizes swamp that of the probability-based sample surveys. Further, the state of sample surveys in the developed world is not healthy. Falling rates of survey participation are linked with ever-inflated costs of data collection. Despite growing needs for information, the creation of new survey vehicles is hampered by strained budgets for official statistical agencies and social science funders. These combined observations are unprecedented challenges for the basic paradigm of inference in the social and economic sciences. This paper discusses alternative ways forward at this moment in history. "
Release date: 2016-03-24
27. Better Adjusted Weights for Respondents in Skewed Populations Archived
Articles and reports: 11-522-X201700014738
Description:
In the standard design approach to missing observations, the construction of weight classes and calibration are used to adjust the design weights for the respondents in the sample. Here we use these adjusted weights to define a Dirichlet distribution which can be used to make inferences about the population. Examples show that the resulting procedures have better performance properties than the standard methods when the population is skewed.
Release date: 2016-03-24
28. Data Science for Dynamic Data Systems: Implications for Official Statistics Archived
Articles and reports: 11-522-X201700014759
Description:
Many of the challenges and opportunities of modern data science have to do with dynamic aspects: evolving populations, the growing volume of administrative and commercial data on individuals and establishments, continuous flows of data and the capacity to analyze and summarize them in real time, and the deterioration of data absent the resources to maintain them. With its emphasis on data quality and supportable results, the domain of Official Statistics is ideal for highlighting statistical and data science issues in a variety of contexts. The messages of the talk include the importance of population frames and their maintenance; the potential for use of multi-frame methods and linkages; how the use of large scale non-survey data as auxiliary information shapes the objects of inference; the complexity of models for large data sets; the importance of recursive methods and regularization; and the benefits of sophisticated data visualization tools in capturing change.
Release date: 2016-03-24
29. Survey Sampling In Official Statistics - Some Thoughts On Directions Archived
Articles and reports: 11-522-X201300014251
Description:
I present a modeller's perspective on the current status quo in official statistics surveys-based inference. In doing so, I try to identify the strengths and weaknesses of the design and model-based inferential positions that survey sampling, at least as far as the official statistics world is concerned, finds itself at present. I close with an example from adaptive survey design that illustrates why taking a model-based perspective (either frequentist or Bayesian) represents the best way for official statistics to avoid the debilitating 'inferential schizophrenia' that seems inevitable if current methodologies are applied to the emerging information requirements of today's world (and possibly even tomorrow's).
Release date: 2014-10-31
30. Explorations in Non-Probability Sampling Using the Web Archived
Articles and reports: 11-522-X201300014252
Description:
Although estimating finite populations characteristics from probability samples has been very successful for large samples, inferences from non-probability samples may also be possible. Non-probability samples have been criticized due to self-selection bias and the lack of methods for estimating the precision of the estimates. The wide spread access to the Web and the ability to do very inexpensive data collection on the Web has reinvigorated interest in this topic. We review of non-probability sampling strategies and summarize some of the key issues. We then propose conditions under which non-probability sampling may be a reasonable approach. We conclude with ideas for future research.
Release date: 2014-10-31

Reference (8)

Reference (8) ((8 results))

1. The Potential Use of Remote Sensing to Produce Field Crop Statistics at Statistics Canada Archived
Surveys and statistical programs – Documentation: 11-522-X201300014259
Description:
In an effort to reduce response burden on farm operators, Statistics Canada is studying alternative approaches to telephone surveys for producing field crop estimates. One option is to publish harvested area and yield estimates in September as is currently done, but to calculate them using models based on satellite and weather data, and data from the July telephone survey. However before adopting such an approach, a method must be found which produces estimates with a sufficient level of accuracy. Research is taking place to investigate different possibilities. Initial research results and issues to consider are discussed in this paper.
Release date: 2014-10-31
2. A note on identifiers in the National Longitudinal Survey of Children and Youth Archived
Surveys and statistical programs – Documentation: 12-002-X20040027035
Description:
As part of the processing of the National Longitudinal Survey of Children and Youth (NLSCY) cycle 4 data, historical revisions have been made to the data of the first 3 cycles, either to correct errors or to update the data. During processing, particular attention was given to the PERSRUK (Person Identifier) and the FIELDRUK (Household Identifier). The same level of attention has not been given to the other identifiers that are included in the data base, the CHILDID (Person identifier) and the _IDHD01 (Household identifier). These identifiers have been created for the public files and can also be found in the master files by default. The PERSRUK should be used to link records between files and the FIELDRUK to determine the household when using the master files.
Release date: 2004-10-05
3. Survey of Financial Security - Methodology for Estimating the Value of Employer Pension Plan Benefits Archived
Surveys and statistical programs – Documentation: 13F0026M2001003
Description:
Initial results from the Survey of Financial Security (SFS), which provides information on the net worth of Canadians, were released on March 15 2001, in The daily. The survey collected information on the value of the financial and non-financial assets owned by each family unit and on the amount of their debt.
Statistics Canada is currently refining this initial estimate of net worth by adding to it an estimate of the value of benefits accrued in employer pension plans. This is an important addition to any asset and debt survey as, for many family units, it is likely to be one of the largest assets. With the aging of the population, information on pension accumulations is greatly needed to better understand the financial situation of those nearing retirement. These updated estimates of the Survey of Financial Security will be released in late fall 2001.
The process for estimating the value of employer pension plan benefits is a complex one. This document describes the methodology for estimating that value, for the following groups: a) persons who belonged to an RPP at the time of the survey (referred to as current plan members); b) persons who had previously belonged to an RPP and either left the money in the plan or transferred it to a new plan; c) persons who are receiving RPP benefits.
This methodology was proposed by Hubert Frenken and Michael Cohen. The former has many years of experience with Statistics Canada working with data on employer pension plans; the latter is a principal with the actuarial consulting firm William M. Mercer. Earlier this year, Statistics Canada carried out a public consultation on the proposed methodology. This report includes updates made as a result of feedback received from data users.
Release date: 2001-09-05
4. Survey of Financial Security - Estimating the Value of Employer Pension Plan Benefits - A Discussion Paper Archived
Surveys and statistical programs – Documentation: 13F0026M2001002
Description:
The Survey of Financial Security (SFS) will provide information on the net worth of Canadians. In order to do this, information was collected - in May and June 1999 - on the value of the assets and debts of each of the families or unattached individuals in the sample. The value of one particular asset is not easy to determine, or to estimate. That is the present value of the amount people have accrued in their employer pension plan. These plans are often called registered pension plans (RPP), as they must be registered with Canada Customs and Revenue Agency. Although some RPP members receive estimates of the value of their accrued benefit, in most cases plan members would not know this amount. However, it is likely to be one of the largest assets for many family units. And, as the baby boomers approach retirement, information on their pension accumulations is much needed to better understand their financial readiness for this transition.
The intent of this paper is to: present, for discussion, a methodology for estimating the present value of employer pension plan benefits for the Survey of Financial Security; and to seek feedback on the proposed methodology. This document proposes a methodology for estimating the value of employer pension plan benefits for the following groups:a) persons who belonged to an RPP at the time of the survey (referred to as current plan members); b) persons who had previously belonged to an RPP and either left the money in the plan or transferred it to a new plan; c) persons who are receiving RPP benefits.
Release date: 2001-02-07
5. The challenges of using administrative data to support policy-relevant research: The example of the longitudinal immigration database (IMDB) Archived
Surveys and statistical programs – Documentation: 11-522-X19990015642
Description:
The Longitudinal Immigration Database (IMDB) links immigration and taxation administrative records into a comprehensive source of data on the labour market behaviour of the landed immigrant population in Canada. It covers the period 1980 to 1995 and will be updated annually starting with the 1996 tax year in 1999. Statistics Canada manages the database on behalf of a federal-provincial consortium led by Citizenship and Immigration Canada. The IMDB was created specifically to respond to the need for detailed and reliable data on the performance and impact of immigration policies and programs. It is the only source of data at Statistics Canada that provides a direct link between immigration policy levers and the economic performance of immigrants. The paper will examine the issues related to the development of a longitudinal database combining administrative records to support policy-relevant research and analysis. Discussion will focus specifically on the methodological, conceptual, analytical and privacy issues involved in the creation and ongoing development of this database. The paper will also touch briefly on research findings, which illustrate the policy outcome links the IMDB allows policy-makers to investigate.
Release date: 2000-03-02
6. The U.S. manufacturing plant ownership change database: Research possibilities Archived
Surveys and statistical programs – Documentation: 11-522-X19990015650
Description:
The U.S. Manufacturing Plant Ownership Change Database (OCD) was constructed using plant-level data taken from the Census Bureau's Longitudinal Research Database (LRD). It contains data on all manufacturing plants that have experienced ownership change at least once during the period 1963-92. This paper reports the status of the OCD and discuss its research possibilities. For an empirical demonstration, data taken from the database are used to study the effects of ownership changes on plant closure.
Release date: 2000-03-02
7. Uncertainties in estimates of radon lung cancer risks Archived
Surveys and statistical programs – Documentation: 11-522-X19990015658
Description:
Radon, a naturally occurring gas found at some level in most homes, is an established risk factor for human lung cancer. The U.S. National Research Council (1999) has recently completed a comprehensive evaluation of the health risks of residential exposure to radon, and developed models for projecting radon lung cancer risks in the general population. This analysis suggests that radon may play a role in the etiology of 10-15% of all lung cancer cases in the United States, although these estimates are subject to considerable uncertainty. In this article, we present a partial analysis of uncertainty and variability in estimates of lung cancer risk due to residential exposure to radon in the United States using a general framework for the analysis of uncertainty and variability that we have developed previously. Specifically, we focus on estimates of the age-specific excess relative risk (ERR) and lifetime relative risk (LRR), both of which vary substantially among individuals.
Release date: 2000-03-02
8. A Comparison of Census Geographic Areas of Canada and the United States Archived
Geographic files and documentation: 92F0138M1993001
Geography: Canada
Description:
The Geography Divisions of Statistics Canada and the U.S. Bureau of the Census have commenced a cooperative research program in order to foster an improved and expanded perspective on geographic areas and their relevance. One of the major objectives is to determine a common geographic area to form a geostatistical basis for cross-border research, analysis and mapping.
This report, which represents the first stage of the research, provides a list of comparable pairs of Canadian and U.S. standard geographic areas based on current definitions. Statistics Canada and the U.S. Bureau of the Census have two basic types of standard geographic entities: legislative/administrative areas (called "legal" entities in the U.S.) and statistical areas.
The preliminary pairing of geographic areas are based on face-value definitions only. The definitions are based on the June 4, 1991 Census of Population and Housing for Canada and the April 1, 1990 Census of Population and Housing for the U.S.A. The important aspect is the overall conceptual comparability, not the precise numerical thresholds used for delineating the areas.
Data users should use this report as a general guide to compare the census geographic areas of Canada and the United States, and should be aware that differences in settlement patterns and population levels preclude a precise one-to-one relationship between conceptually similar areas. The geographic areas compared in this report provide a framework for further empirical research and analysis.
Release date: 1999-03-05

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Date modified:: 2024-04-19