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- Articles and reports: 11-522-X20010016248Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
The Sawmill Survey is a voluntary census of sawmills in Great Britain. It is limited to fixed mills using domestically-grown timber. Three approaches to assess the coverage of this survey are described:
(1) A sample survey of the sawmilling industry from the UK's business register, excluding businesses already sampled in the Sawmill Survey, is used to assess the undercoverage in the list of known sawmills; (2) A non-response follow-up using local knowledge of regional officers of the Forestry Commission, is used to estimate the sawmills that do not respond (mostly the smaller mills); and (3) A survey of small-scale sawmills and mobile sawmills (many of these businesses are micro-enterprises) is conducted to analyse their significance.
These three approaches are synthesized to give an estimate of the coverage of the original survey compared with the total activity identified, and to estimate the importance of micro-enterprises to the sawmilling industry in Great Britain.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016266Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
The key measure of Census quality is the level of response achieved. In recent censuses around the world, this level has been in the high nineties percentage range. This was also true of the 1991 Census in Britain (98%). However, what was particularly noticeable about this Census was the differential response rate and the difficulty in effectively measuring this rate. The United Kingdom set up the One Number Census program in order to research and develop a more effective methodology to measure and account for under-enumeration in the 2001 Census. The key element in this process is the Census Coverage Survey - a significantly larger and redesigned post-enumeration survey.
This paper describes the planning and design of the Census Coverage Survey with particular emphasis on the implementation of the proposed field methodology. It also provides a high-level overview of the success of this survey.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016296Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
The Canadian Labour Force Survey (LFS) is one of Statistics Canada's most important surveys. It is a monthly survey that collects data concerning the person's labour force status, the nature of the person's work or reason for not working, and the person's demographics. The survey sample consists of approximately 52,000 households. Coverage error is a measure of data quality that is important to any survey. One of the key measures of coverage error in the LFS is the percentage difference between the Census of Population estimates and the LFS population counts; this error is called slippage. A negative value indicates that the LFS has a problem of overcoverage, while a positive value indicates the LFS has an undercoverage problem. In general, slippage is positive, thus meaning that the LFS consistently misses people who should be enumerated.
The purpose of this study was to determine why slippage is increasing and what can be done to remedy it. The study was conducted in two stages. The first stage was a historical review of the projects that have studied and tried to control slippage in the LFS, as well as the operational changes that have been implemented over time. The second stage was an analysis of factors such as vacancy rates, non-response, demographics, urban and rural status and the impact of these factors on the slippage rate.
Release date: 2002-09-12 - Articles and reports: 12-001-X20020016419Description:
Since some individuals in a population may lack telephones, telephone surveys using random digit dialling within strata may result in asymptotically biased estimators of ratios. The impact from not being able to sample the non-telephone population is examined. We take into account the propensity that a household owns a telephone, when proposing a post-stratified telephone-weighted estimator, which seems to perform better than the typical post-stratified estimator in terms of mean squared error. Such coverage propensities are estimated using the Public Use Microdata Samples, as provided by the United States Census. Non-post-stratified estimators are considered when sample sizes are small. The asymptotic mean squared error, along with its estimate based on a sample of each of the estimators is derived. Real examples are analysed using the Public Use Microdata Samples. Other forms of no-nresponse are not examined herein.
Release date: 2002-07-05 - Articles and reports: 12-001-X20010026089Description:
Telephone surveys are a convenient and efficient method of data collection. Bias may be introduced into population estimates, however, by the exclusion of nontelephone households from these surveys. Data from the U.S. Federal Communications Commission (FCC) indicates that five and a half to six percent of American households are without phone service at any given time. The bias introduced can be significant since nontelephone households may differ from telephone households in ways that are not adequately handled by poststratification. Many households, called "transients", move in and out of the telephone population during the year, sometimes due to economic reasons or relocation. The transient telephone population may be representative of the nontelephone population in general since its members have recently been in the nontelephone population.
Release date: 2002-02-28
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- Articles and reports: 11-522-X20010016248Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
The Sawmill Survey is a voluntary census of sawmills in Great Britain. It is limited to fixed mills using domestically-grown timber. Three approaches to assess the coverage of this survey are described:
(1) A sample survey of the sawmilling industry from the UK's business register, excluding businesses already sampled in the Sawmill Survey, is used to assess the undercoverage in the list of known sawmills; (2) A non-response follow-up using local knowledge of regional officers of the Forestry Commission, is used to estimate the sawmills that do not respond (mostly the smaller mills); and (3) A survey of small-scale sawmills and mobile sawmills (many of these businesses are micro-enterprises) is conducted to analyse their significance.
These three approaches are synthesized to give an estimate of the coverage of the original survey compared with the total activity identified, and to estimate the importance of micro-enterprises to the sawmilling industry in Great Britain.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016266Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
The key measure of Census quality is the level of response achieved. In recent censuses around the world, this level has been in the high nineties percentage range. This was also true of the 1991 Census in Britain (98%). However, what was particularly noticeable about this Census was the differential response rate and the difficulty in effectively measuring this rate. The United Kingdom set up the One Number Census program in order to research and develop a more effective methodology to measure and account for under-enumeration in the 2001 Census. The key element in this process is the Census Coverage Survey - a significantly larger and redesigned post-enumeration survey.
This paper describes the planning and design of the Census Coverage Survey with particular emphasis on the implementation of the proposed field methodology. It also provides a high-level overview of the success of this survey.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016296Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
The Canadian Labour Force Survey (LFS) is one of Statistics Canada's most important surveys. It is a monthly survey that collects data concerning the person's labour force status, the nature of the person's work or reason for not working, and the person's demographics. The survey sample consists of approximately 52,000 households. Coverage error is a measure of data quality that is important to any survey. One of the key measures of coverage error in the LFS is the percentage difference between the Census of Population estimates and the LFS population counts; this error is called slippage. A negative value indicates that the LFS has a problem of overcoverage, while a positive value indicates the LFS has an undercoverage problem. In general, slippage is positive, thus meaning that the LFS consistently misses people who should be enumerated.
The purpose of this study was to determine why slippage is increasing and what can be done to remedy it. The study was conducted in two stages. The first stage was a historical review of the projects that have studied and tried to control slippage in the LFS, as well as the operational changes that have been implemented over time. The second stage was an analysis of factors such as vacancy rates, non-response, demographics, urban and rural status and the impact of these factors on the slippage rate.
Release date: 2002-09-12 - Articles and reports: 12-001-X20020016419Description:
Since some individuals in a population may lack telephones, telephone surveys using random digit dialling within strata may result in asymptotically biased estimators of ratios. The impact from not being able to sample the non-telephone population is examined. We take into account the propensity that a household owns a telephone, when proposing a post-stratified telephone-weighted estimator, which seems to perform better than the typical post-stratified estimator in terms of mean squared error. Such coverage propensities are estimated using the Public Use Microdata Samples, as provided by the United States Census. Non-post-stratified estimators are considered when sample sizes are small. The asymptotic mean squared error, along with its estimate based on a sample of each of the estimators is derived. Real examples are analysed using the Public Use Microdata Samples. Other forms of no-nresponse are not examined herein.
Release date: 2002-07-05 - Articles and reports: 12-001-X20010026089Description:
Telephone surveys are a convenient and efficient method of data collection. Bias may be introduced into population estimates, however, by the exclusion of nontelephone households from these surveys. Data from the U.S. Federal Communications Commission (FCC) indicates that five and a half to six percent of American households are without phone service at any given time. The bias introduced can be significant since nontelephone households may differ from telephone households in ways that are not adequately handled by poststratification. Many households, called "transients", move in and out of the telephone population during the year, sometimes due to economic reasons or relocation. The transient telephone population may be representative of the nontelephone population in general since its members have recently been in the nontelephone population.
Release date: 2002-02-28
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