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- 1. Network sampling with a bayesian approach ArchivedArticles and reports: 11-522-X20040018730Description:
This paper considers a link-tracing sampling design. It describes the Bayesian approach for the estimation of social network properties and gives an example.
Release date: 2005-10-27 - Articles and reports: 11-522-X20040018733Description:
A survey on injecting drug users is designed to use the information collected from needle exchange centres and from sampled injecting drug users. A methodology is developed to produce various estimates.
Release date: 2005-10-27 - Articles and reports: 11-522-X20040018737Description:
This paper describes methodological factors that may explain variations in disability rates that are produced by various surveys at Statistics Canada. The need for a single "gold standard" estimate as opposed to a set of estimates is discussed.
Release date: 2005-10-27 - Articles and reports: 11-522-X20040018750Description:
This paper modifies the link-tracing sampling with a sequential sample of sites and proposes a maximum likelihood estimator or another one derived under the Bayesian approach. It proposes that confidence intervals be constructed by Bootstrap methods.
Release date: 2005-10-27 - Articles and reports: 11-522-X20040018753Description:
For the estimation of low-income households, a supplementary sample is selected within a limited number of geographic areas. This paper presents the dual sample design used, along with scenarios considered and some findings that led to the choices made.
Release date: 2005-10-27 - Articles and reports: 11-522-X20040018754Description:
For the Survey of Electronic Commerce and Technology, studies are required on rare-event estimation. This paper describes the survey, its main problems and challenges, study findings, and past and future actions.
Release date: 2005-10-27 - Articles and reports: 11-522-X20040018755Description:
This paper reviews the robustness of methods dealing with response errors for rare populations. It also reviews problems with weighting scheme for these populations. It develops an asymptotic framework intended to deal with such problems.
Release date: 2005-10-27 - 8. Domain estimators for the item count technique ArchivedArticles and reports: 12-001-X20050018086Description:
The item count technique, which is an indirect questioning technique, was devised to estimate the proportion of people for whom a sensitive key item holds true. This is achieved by having respondents report the number of descriptive phrases, from a list of several phrases that they believe apply to themselves. The list for half the sample includes the key item, and the list for the other half does not include the key item. The difference in mean number of selected phrases is an estimator of the proportion. In this article, we propose two new methods, referred to as the cross-based method and the double cross-based method, by which proportions in subgroups or domains are estimated based on the data obtained via the item count technique. In order to assess the precision of the proposed methods, we conducted simulation experiments using data obtained from a survey of the Japanese national character. The results illustrate that the double cross-based method is much more accurate than the traditional stratified method, and is less likely to produce illogical estimates.
Release date: 2005-07-21 - Articles and reports: 12-001-X20050018089Description:
We use hierarchical Bayesian models to analyze body mass index (BMI) data of children and adolescents with nonignorable nonresponse from the Third National Health and Nutrition Examination Survey (NHANES III). Our objective is to predict the finite population mean BMI and the proportion of respondents for domains formed by age, race and sex (covariates in the regression models) in each of thirty five large counties, accounting for the nonrespondents. Markov chain Monte Carlo methods are used to fit the models (two selection and two pattern mixture) to the NHANES III BMI data. Using a deviance measure and a cross-validation study, we show that the nonignorable selection model is the best among the four models. We also show that inference about BMI is not too sensitive to the model choice. An improvement is obtained by including a spline regression into the selection model to reflect changes in the relationship between BMI and age.
Release date: 2005-07-21 - Articles and reports: 12-001-X20050018091Description:
Procedures for constructing vectors of nonnegative regression weights are considered. A vector of regression weights in which initial weights are the inverse of the approximate conditional inclusion probabilities is introduced. Through a simulation study, the weighted regression weights, quadratic programming weights, raking ratio weights, weights from logit procedure, and weights of a likelihood-type are compared.
Release date: 2005-07-21
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- 1. Network sampling with a bayesian approach ArchivedArticles and reports: 11-522-X20040018730Description:
This paper considers a link-tracing sampling design. It describes the Bayesian approach for the estimation of social network properties and gives an example.
Release date: 2005-10-27 - Articles and reports: 11-522-X20040018733Description:
A survey on injecting drug users is designed to use the information collected from needle exchange centres and from sampled injecting drug users. A methodology is developed to produce various estimates.
Release date: 2005-10-27 - Articles and reports: 11-522-X20040018737Description:
This paper describes methodological factors that may explain variations in disability rates that are produced by various surveys at Statistics Canada. The need for a single "gold standard" estimate as opposed to a set of estimates is discussed.
Release date: 2005-10-27 - Articles and reports: 11-522-X20040018750Description:
This paper modifies the link-tracing sampling with a sequential sample of sites and proposes a maximum likelihood estimator or another one derived under the Bayesian approach. It proposes that confidence intervals be constructed by Bootstrap methods.
Release date: 2005-10-27 - Articles and reports: 11-522-X20040018753Description:
For the estimation of low-income households, a supplementary sample is selected within a limited number of geographic areas. This paper presents the dual sample design used, along with scenarios considered and some findings that led to the choices made.
Release date: 2005-10-27 - Articles and reports: 11-522-X20040018754Description:
For the Survey of Electronic Commerce and Technology, studies are required on rare-event estimation. This paper describes the survey, its main problems and challenges, study findings, and past and future actions.
Release date: 2005-10-27 - Articles and reports: 11-522-X20040018755Description:
This paper reviews the robustness of methods dealing with response errors for rare populations. It also reviews problems with weighting scheme for these populations. It develops an asymptotic framework intended to deal with such problems.
Release date: 2005-10-27 - 8. Domain estimators for the item count technique ArchivedArticles and reports: 12-001-X20050018086Description:
The item count technique, which is an indirect questioning technique, was devised to estimate the proportion of people for whom a sensitive key item holds true. This is achieved by having respondents report the number of descriptive phrases, from a list of several phrases that they believe apply to themselves. The list for half the sample includes the key item, and the list for the other half does not include the key item. The difference in mean number of selected phrases is an estimator of the proportion. In this article, we propose two new methods, referred to as the cross-based method and the double cross-based method, by which proportions in subgroups or domains are estimated based on the data obtained via the item count technique. In order to assess the precision of the proposed methods, we conducted simulation experiments using data obtained from a survey of the Japanese national character. The results illustrate that the double cross-based method is much more accurate than the traditional stratified method, and is less likely to produce illogical estimates.
Release date: 2005-07-21 - Articles and reports: 12-001-X20050018089Description:
We use hierarchical Bayesian models to analyze body mass index (BMI) data of children and adolescents with nonignorable nonresponse from the Third National Health and Nutrition Examination Survey (NHANES III). Our objective is to predict the finite population mean BMI and the proportion of respondents for domains formed by age, race and sex (covariates in the regression models) in each of thirty five large counties, accounting for the nonrespondents. Markov chain Monte Carlo methods are used to fit the models (two selection and two pattern mixture) to the NHANES III BMI data. Using a deviance measure and a cross-validation study, we show that the nonignorable selection model is the best among the four models. We also show that inference about BMI is not too sensitive to the model choice. An improvement is obtained by including a spline regression into the selection model to reflect changes in the relationship between BMI and age.
Release date: 2005-07-21 - Articles and reports: 12-001-X20050018091Description:
Procedures for constructing vectors of nonnegative regression weights are considered. A vector of regression weights in which initial weights are the inverse of the approximate conditional inclusion probabilities is introduced. Through a simulation study, the weighted regression weights, quadratic programming weights, raking ratio weights, weights from logit procedure, and weights of a likelihood-type are compared.
Release date: 2005-07-21
Reference (1)
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- 1. The Effects of the Revised Estimation Methodology on Estimates from Household Expenditure Surveys ArchivedSurveys and statistical programs – Documentation: 62F0026M2005002Description:
This document will provide an overview of the differences between the old and the new weighting methodologies and the effect of the new weighting system on estimations.
Release date: 2005-06-30
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