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All (14) (0 to 10 of 14 results)
- Articles and reports: 12-001-X200800210761Description:
Optimum stratification is the method of choosing the best boundaries that make strata internally homogeneous, given some sample allocation. In order to make the strata internally homogenous, the strata should be constructed in such a way that the strata variances for the characteristic under study be as small as possible. This could be achieved effectively by having the distribution of the main study variable known and create strata by cutting the range of the distribution at suitable points. If the frequency distribution of the study variable is unknown, it may be approximated from the past experience or some prior knowledge obtained at a recent study. In this paper the problem of finding Optimum Strata Boundaries (OSB) is considered as the problem of determining Optimum Strata Widths (OSW). The problem is formulated as a Mathematical Programming Problem (MPP), which minimizes the variance of the estimated population parameter under Neyman allocation subject to the restriction that sum of the widths of all the strata is equal to the total range of the distribution. The distributions of the study variable are considered as continuous with Triangular and Standard Normal density functions. The formulated MPPs, which turn out to be multistage decision problems, can then be solved using dynamic programming technique proposed by Bühler and Deutler (1975). Numerical examples are presented to illustrate the computational details. The results obtained are also compared with the method of Dalenius and Hodges (1959) with an example of normal distribution.
Release date: 2008-12-23 - 2. Households' use of water and wastewater services ArchivedArticles and reports: 16-002-X200800410752Geography: CanadaDescription:
This article presents data on water conservation and septic system maintenance from the 2006 Households and the Environment Survey. It also compares conservation practices for households using public and private water services.
Release date: 2008-12-09 - Stats in brief: 88-001-X200800710718Description:
This publication presents recent information on the performance and funding of Federal government expenditures on scientific activities, 2008/2009 (intentions). The statistics presented are derived from the survey of science and technology (S&T) activities of federal departments and agencies.
Release date: 2008-11-20 - Stats in brief: 88-001-X200800610707Description:
The information in this document is intended primarily to be used by scientific and technological (S&T) policy makers, both federal and provincial, largely as a basis for inter-provincial and inter-sectoral comparisons. The statistics are aggregates of the provincial government and provincial research organization science surveys conducted by Statistics Canada under contract with the provinces, and cover the period 2002/2003 to 2006/2007.
Release date: 2008-10-17 - Articles and reports: 96-325-X200700010646Geography: CanadaDescription:
Food is as much a necessity as the air we breathe and the water we drink. But do we know where our food comes from, and what it takes to get it into our kitchens? The question of where our food is grown or processed is coming under increased scrutiny, not just in Canada but in other countries, including our trading partners. Concerns underlying this increased focus include discussions of energy consumption required for food transport, environmental concerns, product safety, food security and food costs. The article, Fork in the Road, takes a look at the trade in food and shows how Canadians can find out what foods are being produced in their local area.
Release date: 2008-07-25 - 6. A Bayesian allocation of undecided voters ArchivedArticles and reports: 12-001-X200800110606Description:
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 - 7. A noninformative Bayesian approach to finite population sampling using auxiliary variables ArchivedArticles and reports: 12-001-X200800110611Description:
In finite population sampling prior information is often available in the form of partial knowledge about an auxiliary variable, for example its mean may be known. In such cases, the ratio estimator and the regression estimator are often used for estimating the population mean of the characteristic of interest. The Polya posterior has been developed as a noninformative Bayesian approach to survey sampling. It is appropriate when little or no prior information about the population is available. Here we show that it can be extended to incorporate types of partial prior information about auxiliary variables. We will see that it typically yields procedures with good frequentist properties even in some problems where standard frequentist methods are difficult to apply.
Release date: 2008-06-26 - Articles and reports: 11-622-M2008019Geography: CanadaDescription:
University degree holders in large cities are more prevalent and are growing at a more rapid pace than in smaller cities and rural areas. This relatively high rate of growth stems from net migratory flows and/or higher rates of degree attainment in cities. Using data from the 1996 and 2001 Censuses, this paper tests the relative importance of these two sources of human capital growth by decomposing degree-holder growth across cities into net migratory flows (domestic and foreign) and in situ growth: that is, growth resulting from higher rates of degree attainment among the resident populations of cities. We find that both sources are important, with in situ growth being the more dominant force. Hence, it is less the ability of cities to attract human capital than their ability to generate it that underlies the high rates of degree attainment we observe across city populations.
Release date: 2008-06-02 - 9. An algorithm to differentiate diabetic respondents in the Canadian Community Health Survey ArchivedArticles and reports: 82-003-X200800110533Geography: CanadaDescription:
This article describes an algorithm to classify respondents to cycle 1.1 (2000/2001) of the Canadian Community Health Survey according to whether they have type 1, type 2 or gestational diabetes.
Release date: 2008-03-19 - 10. Robust Bayesian predictive inference for the finite population quantile of a small area ArchivedArticles and reports: 11-522-X200600110392Description:
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
Stats in brief (2)
Stats in brief (2) ((2 results))
- Stats in brief: 88-001-X200800710718Description:
This publication presents recent information on the performance and funding of Federal government expenditures on scientific activities, 2008/2009 (intentions). The statistics presented are derived from the survey of science and technology (S&T) activities of federal departments and agencies.
Release date: 2008-11-20 - Stats in brief: 88-001-X200800610707Description:
The information in this document is intended primarily to be used by scientific and technological (S&T) policy makers, both federal and provincial, largely as a basis for inter-provincial and inter-sectoral comparisons. The statistics are aggregates of the provincial government and provincial research organization science surveys conducted by Statistics Canada under contract with the provinces, and cover the period 2002/2003 to 2006/2007.
Release date: 2008-10-17
Articles and reports (12)
Articles and reports (12) (0 to 10 of 12 results)
- Articles and reports: 12-001-X200800210761Description:
Optimum stratification is the method of choosing the best boundaries that make strata internally homogeneous, given some sample allocation. In order to make the strata internally homogenous, the strata should be constructed in such a way that the strata variances for the characteristic under study be as small as possible. This could be achieved effectively by having the distribution of the main study variable known and create strata by cutting the range of the distribution at suitable points. If the frequency distribution of the study variable is unknown, it may be approximated from the past experience or some prior knowledge obtained at a recent study. In this paper the problem of finding Optimum Strata Boundaries (OSB) is considered as the problem of determining Optimum Strata Widths (OSW). The problem is formulated as a Mathematical Programming Problem (MPP), which minimizes the variance of the estimated population parameter under Neyman allocation subject to the restriction that sum of the widths of all the strata is equal to the total range of the distribution. The distributions of the study variable are considered as continuous with Triangular and Standard Normal density functions. The formulated MPPs, which turn out to be multistage decision problems, can then be solved using dynamic programming technique proposed by Bühler and Deutler (1975). Numerical examples are presented to illustrate the computational details. The results obtained are also compared with the method of Dalenius and Hodges (1959) with an example of normal distribution.
Release date: 2008-12-23 - 2. Households' use of water and wastewater services ArchivedArticles and reports: 16-002-X200800410752Geography: CanadaDescription:
This article presents data on water conservation and septic system maintenance from the 2006 Households and the Environment Survey. It also compares conservation practices for households using public and private water services.
Release date: 2008-12-09 - Articles and reports: 96-325-X200700010646Geography: CanadaDescription:
Food is as much a necessity as the air we breathe and the water we drink. But do we know where our food comes from, and what it takes to get it into our kitchens? The question of where our food is grown or processed is coming under increased scrutiny, not just in Canada but in other countries, including our trading partners. Concerns underlying this increased focus include discussions of energy consumption required for food transport, environmental concerns, product safety, food security and food costs. The article, Fork in the Road, takes a look at the trade in food and shows how Canadians can find out what foods are being produced in their local area.
Release date: 2008-07-25 - 4. A Bayesian allocation of undecided voters ArchivedArticles and reports: 12-001-X200800110606Description:
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 - 5. A noninformative Bayesian approach to finite population sampling using auxiliary variables ArchivedArticles and reports: 12-001-X200800110611Description:
In finite population sampling prior information is often available in the form of partial knowledge about an auxiliary variable, for example its mean may be known. In such cases, the ratio estimator and the regression estimator are often used for estimating the population mean of the characteristic of interest. The Polya posterior has been developed as a noninformative Bayesian approach to survey sampling. It is appropriate when little or no prior information about the population is available. Here we show that it can be extended to incorporate types of partial prior information about auxiliary variables. We will see that it typically yields procedures with good frequentist properties even in some problems where standard frequentist methods are difficult to apply.
Release date: 2008-06-26 - Articles and reports: 11-622-M2008019Geography: CanadaDescription:
University degree holders in large cities are more prevalent and are growing at a more rapid pace than in smaller cities and rural areas. This relatively high rate of growth stems from net migratory flows and/or higher rates of degree attainment in cities. Using data from the 1996 and 2001 Censuses, this paper tests the relative importance of these two sources of human capital growth by decomposing degree-holder growth across cities into net migratory flows (domestic and foreign) and in situ growth: that is, growth resulting from higher rates of degree attainment among the resident populations of cities. We find that both sources are important, with in situ growth being the more dominant force. Hence, it is less the ability of cities to attract human capital than their ability to generate it that underlies the high rates of degree attainment we observe across city populations.
Release date: 2008-06-02 - 7. An algorithm to differentiate diabetic respondents in the Canadian Community Health Survey ArchivedArticles and reports: 82-003-X200800110533Geography: CanadaDescription:
This article describes an algorithm to classify respondents to cycle 1.1 (2000/2001) of the Canadian Community Health Survey according to whether they have type 1, type 2 or gestational diabetes.
Release date: 2008-03-19 - Articles and reports: 11-522-X200600110392Description:
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 - 9. Deterministic and probabilistic record linkage ArchivedArticles and reports: 11-522-X200600110404Description:
Pursuing reduction in cost and response burden in survey programs has led to increased use of information available in administrative databases. Linkages between these two data sources is a way to exploit their complementary nature and maximize their respective usefulness. This paper discusses the various ways we have performed record linkage between the Canadian Community Health Survey (CCHS) and the Health Person-Oriented Information (HPOI) databases. The files resulting from selected linkage methods are used in an analysis of risk factors for having been hospitalized for heart disease. The sensitivity of the analysis with respect to the various linkage approaches is investigated.
Release date: 2008-03-17 - 10. Immigrant populations and myocardial infarctions ArchivedArticles and reports: 11-522-X200600110446Geography: Census metropolitan areaDescription:
Immigrants have health advantages over native-born Canadians, but those advantages are threatened by specific risk situations. This study explores cardiovascular health outcomes in districts of Montréal classified by the proportion of immigrants in the population, using a principal component analysis. The first three components are immigration, degree of socio-economic disadvantage and degree of economic disadvantage. The incidence of myocardial infarction is lower in districts with large immigrant populations than in districts dominated by native-born Canadians. Mortality rates are associated with the degree of socio-economic disadvantage, while revascularization is associated with the proportion of seniors in the population.
Release date: 2008-03-17