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All (197)
All (197) (50 to 60 of 197 results)
- 51. Nonsampling errors in dual frame telephone surveys ArchivedArticles and reports: 12-001-X201100111443Description:
Dual frame telephone surveys are becoming common in the U.S. because of the incompleteness of the landline frame as people transition to cell phones. This article examines nonsampling errors in dual frame telephone surveys. Even though nonsampling errors are ignored in much of the dual frame literature, we find that under some conditions substantial biases may arise in dual frame telephone surveys due to these errors. We specifically explore biases due to nonresponse and measurement error in these telephone surveys. To reduce the bias resulting from these errors, we propose dual frame sampling and weighting methods. The compositing factor for combining the estimates from the two frames is shown to play an important role in reducing nonresponse bias.
Release date: 2011-06-29 - 52. Maximum likelihood estimation for contingency tables and logistic regression with incorrectly linked data ArchivedArticles and reports: 12-001-X201100111444Description:
Data linkage is the act of bringing together records that are believed to belong to the same unit (e.g., person or business) from two or more files. It is a very common way to enhance dimensions such as time and breadth or depth of detail. Data linkage is often not an error-free process and can lead to linking a pair of records that do not belong to the same unit. There is an explosion of record linkage applications, yet there has been little work on assuring the quality of analyses using such linked files. Naively treating such a linked file as if it were linked without errors will, in general, lead to biased estimates. This paper develops a maximum likelihood estimator for contingency tables and logistic regression with incorrectly linked records. The estimation technique is simple and is implemented using the well-known EM algorithm. A well known method of linking records in the present context is probabilistic data linking. The paper demonstrates the effectiveness of the proposed estimators in an empirical study which uses probabilistic data linkage.
Release date: 2011-06-29 - 53. Hierarchical Bayes small area estimation under a spatial model with application to health survey data ArchivedArticles and reports: 12-001-X201100111445Description:
In this paper we study small area estimation using area level models. We first consider the Fay-Herriot model (Fay and Herriot 1979) for the case of smoothed known sampling variances and the You-Chapman model (You and Chapman 2006) for the case of sampling variance modeling. Then we consider hierarchical Bayes (HB) spatial models that extend the Fay-Herriot and You-Chapman models by capturing both the geographically unstructured heterogeneity and spatial correlation effects among areas for local smoothing. The proposed models are implemented using the Gibbs sampling method for fully Bayesian inference. We apply the proposed models to the analysis of health survey data and make comparisons among the HB model-based estimates and direct design-based estimates. Our results have shown that the HB model-based estimates perform much better than the direct estimates. In addition, the proposed area level spatial models achieve smaller CVs than the Fay-Herriot and You-Chapman models, particularly for the areas with three or more neighbouring areas. Bayesian model comparison and model fit analysis are also presented.
Release date: 2011-06-29 - Articles and reports: 12-001-X201100111446Description:
Small area estimation based on linear mixed models can be inefficient when the underlying relationships are non-linear. In this paper we introduce SAE techniques for variables that can be modelled linearly following a non-linear transformation. In particular, we extend the model-based direct estimator of Chandra and Chambers (2005, 2009) to data that are consistent with a linear mixed model in the logarithmic scale, using model calibration to define appropriate weights for use in this estimator. Our results show that the resulting transformation-based estimator is both efficient and robust with respect to the distribution of the random effects in the model. An application to business survey data demonstrates the satisfactory performance of the method.
Release date: 2011-06-29 - Articles and reports: 12-001-X201100111447Description:
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-X201100111448Description:
In two-phase sampling for stratification, the second-phase sample is selected by a stratified sample based on the information observed in the first-phase sample. We develop a replication-based bias adjusted variance estimator that extends the method of Kim, Navarro and Fuller (2006). The proposed method is also applicable when the first-phase sampling rate is not negligible and when second-phase sample selection is unequal probability Poisson sampling within each stratum. The proposed method can be extended to variance estimation for two-phase regression estimators. Results from a limited simulation study are presented.
Release date: 2011-06-29 - 57. Cost efficiency of repeated cluster surveys ArchivedArticles and reports: 12-001-X201100111449Description:
We analyze the statistical and economic efficiency of different designs of cluster surveys collected in two consecutive time periods, or waves. In an independent design, two cluster samples in two waves are taken independently from one another. In a cluster-panel design, the same clusters are used in both waves, but samples within clusters are taken independently in two time periods. In an observation-panel design, both clusters and observations are retained from one wave of data collection to another. By assuming a simple population structure, we derive design variances and costs of the surveys conducted according to these designs. We first consider a situation in which the interest lies in estimation of the change in the population mean between two time periods, and derive the optimal sample allocations for the three designs of interest. We then propose the utility maximization framework borrowed from microeconomics to illustrate a possible approach to the choice of the design that strives to optimize several variances simultaneously. Incorporating the contemporaneous means and their variances tends to shift the preferences from observation-panel towards simpler panel-cluster and independent designs if the panel mode of data collection is too expensive. We present numeric illustrations demonstrating how a survey designer may want to choose the efficient design given the population parameters and data collection cost.
Release date: 2011-06-29 - Articles and reports: 12-001-X201100111450Description:
This paper examines the efficiency of the Horvitz-Thompson estimator from a systematic probability proportional to size (PPS) sample drawn from a randomly ordered list. In particular, the efficiency is compared with that of an ordinary ratio estimator. The theoretical results are confirmed empirically with of a simulation study using Dutch data from the Producer Price Index.
Release date: 2011-06-29 - Articles and reports: 12-001-X201100111451Description:
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 - 60. Low Income Lines, 2009-2010 ArchivedArticles and reports: 75F0002M2011002Description:
In order to provide a holographic or complete picture of low income, Statistics Canada uses three complementary low income lines: the Low Income Cut-offs (LICOs), the Low Income Measures (LIMs) and the Market Basket Measure (MBM). While the first two lines were developed by Statistics Canada, the MBM is based on concepts developed by Human Resources and Skill Development Canada. Though these measures differ from one another, they give a generally consistent picture of low income status over time. None of these measures is the best. Each contributes its own perspective and its own strengths to the study of low income, so that cumulatively, the three provide a better understanding of the phenomenon of low income as a whole. These measures are not measures of poverty, but strictly measures of low income.
Release date: 2011-06-15
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Analysis (197)
Analysis (197) (20 to 30 of 197 results)
- 21. Hiring and Layoff Rates by Economic Region of Residence: Data Quality, Concepts and Methods ArchivedArticles and reports: 11-633-X2016001Description:
Every year, thousands of workers lose their jobs as firms reduce the size of their workforce in response to growing competition, technological changes, changing trade patterns and numerous other factors. Thousands of workers also start a job with a new employer as new firms enter a product market and existing firms expand or replace employees who recently left. This worker reallocation process across employers is generally seen as contributing to productivity growth and rising living standards. To measure this labour reallocation process, labour market indicators such as hiring rates and layoff rates are needed. In response to growing demand for subprovincial labour market information and taking advantage of unique administrative datasets, Statistics Canada is producing hiring rates and layoff rates by economic region of residence. This document describes the data sources, conceptual and methodological issues, and other matters pertaining to these two indicators.
Release date: 2016-06-27 - 22. Do Workplace Pensions Crowd Out Other Retirement Savings? Evidence from Canadian Tax Records ArchivedArticles and reports: 11F0019M2015371Description:
This paper investigates whether registered pension plans (RPPs) help households prepare financially for retirement or simply substitute for other forms of private saving. This issue is addressed using a panel of 1.8 million Canadian households, from 1991 to 2010, which appear in the Longitudinal Administrative Databank. The analysis controls for correlations in savings across accounts due to unobserved tastes for saving by exploiting the fact that employer contribution rates increase discontinuously on earnings above the average industrial wage, a unique feature of occupational pensions in Canada, the effect being estimated in a Regression Kink Design.
Release date: 2015-12-21 - 23. The feasibility of adding treatment data to the Canadian Cancer Registry using record linkage ArchivedArticles and reports: 82-622-X2015009Description:
The Canadian Cancer Registry (CCR) represents a collaborative effort between Statistics Canada and the thirteen provincial and territorial cancer registries to create a single database to report annually on cancer incidence and survival at the national and jurisdictional level. While gains have been made to ensure high quality, standardized, and comparable data, the CCR currently lacks information on cancer treatment. The Canadian Council of Cancer Registries (CCCR) identified the need to capture treatment data at the national level as a key strategic priority for 2013/2014. Record linkage was identified as one possible approach to fill this information gap.
The purpose of this study is to examine the feasibility of using record linkage to add cancer treatment information for selected cancers: breast, colorectal and prostate. The objectives are twofold: to assess the quality of the linkage processes and the validity of using linked data to estimate cancer treatment rates at the provincial level. The study is based on the Canadian Cancer Registry (2005 to 2008) linked to the Discharge Abstract Database (DAD) and the National Ambulatory Care Reporting System (NACRS) for four provinces (Ontario, Manitoba, Nova Scotia and Prince Edward Island). The linkage was proposed by Statistics Canada, the CCCR and the Canadian Institute for Health Information (CIHI). The linkage was approved and conducted at Statistics Canada.
Release date: 2015-11-23 - Articles and reports: 82-003-X201501114243Description:
A surveillance tool was developed to assess dietary intake collected by surveys in relation to Eating Well with Canada’s Food Guide (CFG). The tool classifies foods in the Canadian Nutrient File (CNF) according to how closely they reflect CFG. This article describes the validation exercise conducted to ensure that CNF foods determined to be “in line with CFG” were appropriately classified.
Release date: 2015-11-18 - Articles and reports: 13-605-X201500914239Description: This paper outlines the methodology being used to integrate the value of selected natural resource assets into the quarterly sectored national balance sheet accounts. It responds to recommendations in the revised United Nations System of National Accounts to include these values in the balance sheet. The addition of these asset values will significantly increase and improve measures of sectoral net worth.Release date: 2015-11-17
- 26. Demosim 2015 ArchivedArticles and reports: 91-621-X2015001Description:
This document briefly describes Demosim, the microsimulation population projection model, how it works as well as its methods and data sources. It is a methodological complement to the analytical products produced using Demosim.
Release date: 2015-09-17 - 27. Walk Score® and the prevalence of utilitarian walking and obesity among Ontario adults: A cross-sectional study ArchivedArticles and reports: 82-003-X201500714204Description:
The objective of this study was to determine if the prevalence of overweight and obesity is associated with neighbourhood walkability. The analysis tested whether a dose-response relationship between the Street Smart Walk Score® and various measures of physical activity, overweight, and obesity existed in a large, population-based sample of adults in urban and suburban Ontario.
Release date: 2015-07-15 - Articles and reports: 82-003-X201500714205Description:
Discrepancies between self-reported and objectively measured physical activity are well-known. For the purpose of validation, this study compares a new self-reported physical activity questionnaire with an existing one and with accelerometer data.
Release date: 2015-07-15 - Articles and reports: 82-003-X201500714206Description:
The 2012/2013 Canadian Health Measures Survey collected audiometric and self-reported data to estimate the prevalence of hearing loss and limitations in a population-based sample of Canadians. This study presents an analysis of CHMS audiometric and self-reported hearing data for adults aged 20 to 79.
Release date: 2015-07-15 - Articles and reports: 82-003-X201500514169Description:
The Cancer Risk Management Model incorporates the risk of developing cancer, disease screening and clinical management with cost and labour data to assess health outcomes and economic impact. A screening module added to the lung cancer module enables a variety of scenarios to be evaluated for different target populations with varying rates of participation, compliance, and frequency of low-dose computed tomography screening.
Release date: 2015-05-20
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