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All (11) (0 to 10 of 11 results)

  • Surveys and statistical programs – Documentation: 81-582-G
    Description: This handbook complements the tables of the Pan-Canadian Education Indicators Program (PCEIP). It is a guide that provides general descriptions for each indicator and indicator component. PCEIP has five broad indicator sets: a portrait of the school-age population; financing education systems; elementary and secondary education; postsecondary education; and transitions and outcomes.

    The Pan-Canadian Education Indicators Program (PCEIP) is a joint venture of Statistics Canada and the Council of Ministers of Education, Canada.

    Release date: 2024-03-28

  • Articles and reports: 18-001-X2017002
    Description:

    This working paper presents a methodology to measure remoteness at the community level. The method takes into account some of the recent literature on the subject, as well as new computational opportunities provided by the integration of official statistics with data from non-official statistical sources. The approach that was used in the computations accounts for multiple points of access to services; it also establishes a continuum between communities with different transportation infrastructures and connectivity while at the same time retaining the information on the community transportation infrastructures in the database. In addition, a method to implement accessibility measures to selected services is also outlined and a sample of accessibility measures are computed.

    Release date: 2017-05-09

  • Articles and reports: 12-001-X201500214238
    Description:

    Félix-Medina and Thompson (2004) proposed a variant of link-tracing sampling to sample hidden and/or hard-to-detect human populations such as drug users and sex workers. In their variant, an initial sample of venues is selected and the people found in the sampled venues are asked to name other members of the population to be included in the sample. Those authors derived maximum likelihood estimators of the population size under the assumption that the probability that a person is named by another in a sampled venue (link-probability) does not depend on the named person (homogeneity assumption). In this work we extend their research to the case of heterogeneous link-probabilities and derive unconditional and conditional maximum likelihood estimators of the population size. We also propose profile likelihood and bootstrap confidence intervals for the size of the population. The results of simulations studies carried out by us show that in presence of heterogeneous link-probabilities the proposed estimators perform reasonably well provided that relatively large sampling fractions, say larger than 0.5, be used, whereas the estimators derived under the homogeneity assumption perform badly. The outcomes also show that the proposed confidence intervals are not very robust to deviations from the assumed models.

    Release date: 2015-12-17

  • Articles and reports: 12-001-X201200111682
    Description:

    Sample allocation issues are studied in the context of estimating sub-population (stratum or domain) means as well as the aggregate population mean under stratified simple random sampling. A non-linear programming method is used to obtain "optimal" sample allocation to strata that minimizes the total sample size subject to specified tolerances on the coefficient of variation of the estimators of strata means and the population mean. The resulting total sample size is then used to determine sample allocations for the methods of Costa, Satorra and Ventura (2004) based on compromise allocation and Longford (2006) based on specified "inferential priorities". In addition, we study sample allocation to strata when reliability requirements for domains, cutting across strata, are also specified. Performance of the three methods is studied using data from Statistics Canada's Monthly Retail Trade Survey (MRTS) of single establishments.

    Release date: 2012-06-27

  • Articles and reports: 12-001-X201100111447
    Description:

    This paper introduces a R-package for the stratification of a survey population using a univariate stratification variable X and for the calculation of stratum sample sizes. Non iterative methods such as the cumulative root frequency method and the geometric stratum boundaries are implemented. Optimal designs, with stratum boundaries that minimize either the CV of the simple expansion estimator for a fixed sample size n or the n value for a fixed CV can be constructed. Two iterative algorithms are available to find the optimal stratum boundaries. The design can feature a user defined certainty stratum where all the units are sampled. Take-all and take-none strata can be included in the stratified design as they might lead to smaller sample sizes. The sample size calculations are based on the anticipated moments of the survey variable Y, given the stratification variable X. The package handles conditional distributions of Y given X that are either a heteroscedastic linear model, or a log-linear model. Stratum specific non-response can be accounted for in the design construction and in the sample size calculations.

    Release date: 2011-06-29

  • Articles and reports: 12-001-X201000211385
    Description:

    In this short note, we show that simple random sampling without replacement and Bernoulli sampling have approximately the same entropy when the population size is large. An empirical example is given as an illustration.

    Release date: 2010-12-21

  • Articles and reports: 12-001-X200700210495
    Description:

    The purpose of this work is to obtain reliable estimates in study domains when there are potentially very small sample sizes and the sampling design stratum differs from the study domain. The population sizes are unknown as well for both the study domain and the sampling design stratum. In calculating parameter estimates in the study domains, a random sample size is often necessary. We propose a new family of generalized linear mixed models with correlated random effects when there is more than one unknown parameter. The proposed model will estimate both the population size and the parameter of interest. General formulae for full conditional distributions required for Markov chain Monte Carlo (MCMC) simulations are given for this framework. Equations for Bayesian estimation and prediction at the study domains are also given. We apply the 1998 Missouri Turkey Hunting Survey, which stratified samples based on the hunter's place of residence and we require estimates at the domain level, defined as the county in which the turkey hunter actually hunted.

    Release date: 2008-01-03

  • Articles and reports: 21-601-M2002060
    Description:

    This research project provides an overview of diversification and specialization in rural regions and communities for the census years 1981, 1986, 1991 and 1996.

    Release date: 2002-12-04

  • Articles and reports: 12-001-X20000025531
    Description:

    Information from list and area sampling frames is combined to obtain efficient estimates of population size and totals. We consider the case where the probabilities of inclusion on the list frames are heterogeneous and are modeled as a function of covariates. We adapt and modify the methodology of Huggins (1989) and Albo (1990) for modeling auxiliary variables in capture-recapture studies using a logistic regression model. We present the results from a simulation study which compares various estimators of frame size and population totals using the logistic regression approach to modeling heterogeneous inclusion probabilities.

    Release date: 2001-02-28

  • Table: 85-223-X
    Description:

    This report presents summary crime statistics as well as police personnel and expenditures for all municipal police departments in Canada. The report is organized by province and by city-size within province. Data include violent and property crime rates, clearance rates, population per officer and per capita costs.

    Release date: 1998-12-21
Data (1)

Data (1) ((1 result))

  • Table: 85-223-X
    Description:

    This report presents summary crime statistics as well as police personnel and expenditures for all municipal police departments in Canada. The report is organized by province and by city-size within province. Data include violent and property crime rates, clearance rates, population per officer and per capita costs.

    Release date: 1998-12-21
Analysis (9)

Analysis (9) ((9 results))

  • Articles and reports: 18-001-X2017002
    Description:

    This working paper presents a methodology to measure remoteness at the community level. The method takes into account some of the recent literature on the subject, as well as new computational opportunities provided by the integration of official statistics with data from non-official statistical sources. The approach that was used in the computations accounts for multiple points of access to services; it also establishes a continuum between communities with different transportation infrastructures and connectivity while at the same time retaining the information on the community transportation infrastructures in the database. In addition, a method to implement accessibility measures to selected services is also outlined and a sample of accessibility measures are computed.

    Release date: 2017-05-09

  • Articles and reports: 12-001-X201500214238
    Description:

    Félix-Medina and Thompson (2004) proposed a variant of link-tracing sampling to sample hidden and/or hard-to-detect human populations such as drug users and sex workers. In their variant, an initial sample of venues is selected and the people found in the sampled venues are asked to name other members of the population to be included in the sample. Those authors derived maximum likelihood estimators of the population size under the assumption that the probability that a person is named by another in a sampled venue (link-probability) does not depend on the named person (homogeneity assumption). In this work we extend their research to the case of heterogeneous link-probabilities and derive unconditional and conditional maximum likelihood estimators of the population size. We also propose profile likelihood and bootstrap confidence intervals for the size of the population. The results of simulations studies carried out by us show that in presence of heterogeneous link-probabilities the proposed estimators perform reasonably well provided that relatively large sampling fractions, say larger than 0.5, be used, whereas the estimators derived under the homogeneity assumption perform badly. The outcomes also show that the proposed confidence intervals are not very robust to deviations from the assumed models.

    Release date: 2015-12-17

  • Articles and reports: 12-001-X201200111682
    Description:

    Sample allocation issues are studied in the context of estimating sub-population (stratum or domain) means as well as the aggregate population mean under stratified simple random sampling. A non-linear programming method is used to obtain "optimal" sample allocation to strata that minimizes the total sample size subject to specified tolerances on the coefficient of variation of the estimators of strata means and the population mean. The resulting total sample size is then used to determine sample allocations for the methods of Costa, Satorra and Ventura (2004) based on compromise allocation and Longford (2006) based on specified "inferential priorities". In addition, we study sample allocation to strata when reliability requirements for domains, cutting across strata, are also specified. Performance of the three methods is studied using data from Statistics Canada's Monthly Retail Trade Survey (MRTS) of single establishments.

    Release date: 2012-06-27

  • Articles and reports: 12-001-X201100111447
    Description:

    This paper introduces a R-package for the stratification of a survey population using a univariate stratification variable X and for the calculation of stratum sample sizes. Non iterative methods such as the cumulative root frequency method and the geometric stratum boundaries are implemented. Optimal designs, with stratum boundaries that minimize either the CV of the simple expansion estimator for a fixed sample size n or the n value for a fixed CV can be constructed. Two iterative algorithms are available to find the optimal stratum boundaries. The design can feature a user defined certainty stratum where all the units are sampled. Take-all and take-none strata can be included in the stratified design as they might lead to smaller sample sizes. The sample size calculations are based on the anticipated moments of the survey variable Y, given the stratification variable X. The package handles conditional distributions of Y given X that are either a heteroscedastic linear model, or a log-linear model. Stratum specific non-response can be accounted for in the design construction and in the sample size calculations.

    Release date: 2011-06-29

  • Articles and reports: 12-001-X201000211385
    Description:

    In this short note, we show that simple random sampling without replacement and Bernoulli sampling have approximately the same entropy when the population size is large. An empirical example is given as an illustration.

    Release date: 2010-12-21

  • Articles and reports: 12-001-X200700210495
    Description:

    The purpose of this work is to obtain reliable estimates in study domains when there are potentially very small sample sizes and the sampling design stratum differs from the study domain. The population sizes are unknown as well for both the study domain and the sampling design stratum. In calculating parameter estimates in the study domains, a random sample size is often necessary. We propose a new family of generalized linear mixed models with correlated random effects when there is more than one unknown parameter. The proposed model will estimate both the population size and the parameter of interest. General formulae for full conditional distributions required for Markov chain Monte Carlo (MCMC) simulations are given for this framework. Equations for Bayesian estimation and prediction at the study domains are also given. We apply the 1998 Missouri Turkey Hunting Survey, which stratified samples based on the hunter's place of residence and we require estimates at the domain level, defined as the county in which the turkey hunter actually hunted.

    Release date: 2008-01-03

  • Articles and reports: 21-601-M2002060
    Description:

    This research project provides an overview of diversification and specialization in rural regions and communities for the census years 1981, 1986, 1991 and 1996.

    Release date: 2002-12-04

  • Articles and reports: 12-001-X20000025531
    Description:

    Information from list and area sampling frames is combined to obtain efficient estimates of population size and totals. We consider the case where the probabilities of inclusion on the list frames are heterogeneous and are modeled as a function of covariates. We adapt and modify the methodology of Huggins (1989) and Albo (1990) for modeling auxiliary variables in capture-recapture studies using a logistic regression model. We present the results from a simulation study which compares various estimators of frame size and population totals using the logistic regression approach to modeling heterogeneous inclusion probabilities.

    Release date: 2001-02-28

  • Articles and reports: 12-001-X19980013912
    Description:

    Efficient estimates of population size and totals based on information from multiple list frames and an independent area frame are considered. This work is an extension of the methodology proposed by Harley (1962) which considers two general frames. A main disadvantage of list frames is that they are typically incomplete. In this paper, we propose several methods to address frame deficiencies. A joint list-area sampling design incorporates multiple frames and achieves full coverage of the target population. For each combination of frames, we present the appropriate notation, likelihood function, and parameter estimators. Results from a simulation study that compares the various properties of the proposed estimators are also presented.

    Release date: 1998-07-31
Reference (1)

Reference (1) ((1 result))

  • Surveys and statistical programs – Documentation: 81-582-G
    Description: This handbook complements the tables of the Pan-Canadian Education Indicators Program (PCEIP). It is a guide that provides general descriptions for each indicator and indicator component. PCEIP has five broad indicator sets: a portrait of the school-age population; financing education systems; elementary and secondary education; postsecondary education; and transitions and outcomes.

    The Pan-Canadian Education Indicators Program (PCEIP) is a joint venture of Statistics Canada and the Council of Ministers of Education, Canada.

    Release date: 2024-03-28
Date modified: