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All (197) (50 to 60 of 197 results)

51. Nonsampling errors in dual frame telephone surveys Archived
Articles and reports: 12-001-X201100111443
Description:
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 Archived
Articles and reports: 12-001-X201100111444
Description:
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 Archived
Articles and reports: 12-001-X201100111445
Description:
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
54. Small area estimation under transformation to linearity Archived
Articles and reports: 12-001-X201100111446
Description:
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
55. The construction of stratified designs in R with the package stratification Archived
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
56. Replication variance estimation under two-phase sampling Archived
Articles and reports: 12-001-X201100111448
Description:
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 Archived
Articles and reports: 12-001-X201100111449
Description:
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
58. On the efficiency of randomized probability proportional to size sampling Archived
Articles and reports: 12-001-X201100111450
Description:
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
59. 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
60. Low Income Lines, 2009-2010 Archived
Articles and reports: 75F0002M2011002
Description:
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) (40 to 50 of 197 results)

41. Estimating agreement coefficients from sample survey data Archived
Articles and reports: 12-001-X201200111686
Description:
We present a generalized estimating equations approach for estimating the concordance correlation coefficient and the kappa coefficient from sample survey data. The estimates and their accompanying standard error need to correctly account for the sampling design. Weighted measures of the concordance correlation coefficient and the kappa coefficient, along with the variance of these measures accounting for the sampling design, are presented. We use the Taylor series linearization method and the jackknife procedure for estimating the standard errors of the resulting parameter estimates. Body measurement and oral health data from the Third National Health and Nutrition Examination Survey are used to illustrate this methodology.
Release date: 2012-06-27
42. Cities and Growth: Moving to Toronto - Income Gains Associated with Large Metropolitan Labour Markets Archived
Articles and reports: 11-622-M2012023
Geography: Canada
Description:
This paper examines the process by which migrants experience gains in earnings subsequent to migration and, in particular, the advantage that migrants obtain from moving to large, dynamic metropolitan labour markets, using Toronto as a benchmark. There are two potentially distinct patterns to gains in earnings associated with migration. The first is a step upwards in which workers realize immediate gains in earnings subsequent to migration. The second is accelerated gains in earnings subsequent to migration. Immediate gains are associated with obtaining a position in a more productive firm and/or a better match between worker skills and abilities and job tasks. Accelerated gains in earnings are associated processes that take time, such as learning or job switching as workers and firms seek out better matches. Evaluated here is the expectation that the economies of large metropolitan areas provide workers with an initial productive advantage stemming from a one-time improvement in worker productivity and/or a dynamic that accelerates gains in earnings over time through the potentially entwined processes of learning and matching. A variety of datasets and methodologies, including propensity score matching, are used to evaluate patterns of income gains associated with migration to Toronto.
Release date: 2012-05-03
43. Geozones: An area-based method for analysis of health outcomes Archived
Articles and reports: 82-003-X201200111633
Geography: Canada
Description:
This paper explains the methodology for creating Geozones, which are area-based thresholds of population characteristics derived from census data, which can be used in the analysis of social or economic differences in health and health service utilization.
Release date: 2012-03-21
44. Do Relative Canada/U.S. Prices Equate to the Exchange Rate? Archived
Articles and reports: 11-626-X2012003
Geography: Canada
Description:
This Economic Insight discusses price differences between Canada and the United States. It is based on the concepts and methods from Statistics Canada's Purchasing Power Parity program.
Release date: 2012-01-04
45. Variance estimation under composite imputation: The methodology behind SEVANI Archived
Articles and reports: 12-001-X201100211605
Description:
Composite imputation is often used in business surveys. The term "composite" means that more than a single imputation method is used to impute missing values for a variable of interest. The literature on variance estimation in the presence of composite imputation is rather limited. To deal with this problem, we consider an extension of the methodology developed by Särndal (1992). Our extension is quite general and easy to implement provided that linear imputation methods are used to fill in the missing values. This class of imputation methods contains linear regression imputation, donor imputation and auxiliary value imputation, sometimes called cold-deck or substitution imputation. It thus covers the most common methods used by national statistical agencies for the imputation of missing values. Our methodology has been implemented in the System for the Estimation of Variance due to Nonresponse and Imputation (SEVANI) developed at Statistics Canada. Its performance is evaluated in a simulation study.
Release date: 2011-12-21
46. Adaptive network and spatial sampling Archived
Articles and reports: 12-001-X201100211607
Description:
This paper describes recent developments in adaptive sampling strategies and introduces new variations on those strategies. Recent developments described included targeted random walk designs and adaptive web sampling. These designs are particularly suited for sampling in networks; for example, for finding a sample of people from a hidden human population by following social links from sample individuals to find additional members of the hidden population to add to the sample. Each of these designs can also be translated into spatial settings to produce flexible new spatial adaptive strategies for sampling unevenly distributed populations. Variations on these sampling strategies include versions in which the network or spatial links have unequal weights and are followed with unequal probabilities.
Release date: 2011-12-21
47. Ten years of balanced sampling with the cube method: An appraisal Archived
Articles and reports: 12-001-X201100211609
Description:
This paper presents a review and assessment of the use of balanced sampling by means of the cube method. After defining the notion of balanced sample and balanced sampling, a short history of the concept of balancing is presented. The theory of the cube method is briefly presented. Emphasis is placed on the practical problems posed by balanced sampling: the interest of the method with respect to other sampling methods and calibration, the field of application, the accuracy of balancing, the choice of auxiliary variables and ways to implement the method.
Release date: 2011-12-21
48. Innovations in survey sampling design: Discussion of three contributions presented at the U.S. Census Bureau Archived
Articles and reports: 12-001-X201100211610
Description:
In this paper, a discussion of the three papers from the US Census Bureau special compilation is presented.
Release date: 2011-12-21
49. A Profile of Canadian Importers, 2002 to 2009 Archived
Articles and reports: 65-507-M2011011
Description:
This issue presents statistics, derived from the Importer Register Database, on importing establishments for the years 2002 to 2009. This Importer Register Database provides importer statistics such as the number of importers and the value of their imports by industry, importer size, origin and province of residence.
The establishment is the statistical unit of measure. Consequently, any reference made here to "importers" represents "statistical establishments that imported." Inclusion in the database requires that an establishment has imported merchandise in at least one year from 2002 to 2009. If an establishment does not import in a given year, that establishment is not included in the Register for that year.
This report is divided into four sections: "Highlights" consist of an overview of results of the 2009 Importer Register Database; "Findings" contains more detailed analyses of the Importer Register Database; "Methodology, Data concepts and definitions" outlines the estimation methods and limitations as well as the fundamental principles of the Importer Register Database; and "Data tables" contain tabular data for the years from 2002 to 2009.
Release date: 2011-12-06
50. A Profile of Canadian Exporters, 1996 to 2009 Archived
Articles and reports: 65-507-M2010010
Geography: Province or territory
Description:
This issue presents exporter statistics from 1996 to 2009 including the number of exporters, the value of their domestic exports by industry, exporter size, destination and province of residence as well as employment statistics of exporting establishments for the year 2009. The data in this issue are at the establishment level and are derived from the Exporter Register Database.
Release date: 2011-10-28

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Date modified:: 2024-06-09