Frames and coverage
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- Articles and reports: 75F0002M2023001Description: This discussion paper describes the work being achieved and undertaken by Statistics Canada, in partnership with the Treasury Board of Canada Secretariat, the Department of Finance Canada and the Privy Council Office, on developing the Quality of Life Framework for Canada and related outputs, including an online Hub. This is the first paper in a series that will provide updates on the progress of work relating to the Framework.Release date: 2023-04-19
- Articles and reports: 36-28-0001202300100003Description: Quality of life and well-being research often involves survey content that is subjective in nature, for example questions pertaining to life satisfaction. Two phenomena impacting responses to self-reported life satisfaction are studied across a range of social surveys: the framing effect, where a respondent’s answer is influenced by the theme of the survey or its content; and the mode effect, where a respondent’s answer is influenced by the method in which survey data is collected (with an interviewer, through an online collection portal, etc.). The objective of this paper is to document the effect that survey collection and survey content have on Canadians’ self-reported satisfaction with their lives. The impact of these effects on life satisfaction responses is measured across three Statistics Canada survey series: the General Social Survey, the Canadian Community Health Survey, and the Canadian Social Survey.Release date: 2023-01-25
- Articles and reports: 12-001-X201900300008Description:
Dual frame surveys are useful when no single frame with adequate coverage exists. However estimators from dual frame designs require knowledge of the frame memberships of each sampled unit. When this information is not available from the frame itself, it is often collected from the respondent. When respondents provide incorrect membership information, the resulting estimators of means or totals can be biased. A method for reducing this bias, using accurate membership information obtained about a subsample of respondents, is proposed. The properties of the new estimator are examined and compared to alternative estimators. The proposed estimator is applied to the data from the motivating example, which was a recreational angler survey, using an address frame and an incomplete fishing license frame.
Release date: 2019-12-17 - Articles and reports: 12-001-X201500114149Description:
This paper introduces a general framework for deriving the optimal inclusion probabilities for a variety of survey contexts in which disseminating survey estimates of pre-established accuracy for a multiplicity of both variables and domains of interest is required. The framework can define either standard stratified or incomplete stratified sampling designs. The optimal inclusion probabilities are obtained by minimizing costs through an algorithm that guarantees the bounding of sampling errors at the domains level, assuming that the domain membership variables are available in the sampling frame. The target variables are unknown, but can be predicted with suitable super-population models. The algorithm takes properly into account this model uncertainty. Some experiments based on real data show the empirical properties of the algorithm.
Release date: 2015-06-29 - Articles and reports: 12-001-X201400214128Description:
Users, funders and providers of official statistics want estimates that are “wider, deeper, quicker, better, cheaper” (channeling Tim Holt, former head of the UK Office for National Statistics), to which I would add “more relevant” and “less burdensome”. Since World War II, we have relied heavily on the probability sample survey as the best we could do - and that best being very good - to meet these goals for estimates of household income and unemployment, self-reported health status, time use, crime victimization, business activity, commodity flows, consumer and business expenditures, et al. Faced with secularly declining unit and item response rates and evidence of reporting error, we have responded in many ways, including the use of multiple survey modes, more sophisticated weighting and imputation methods, adaptive design, cognitive testing of survey items, and other means to maintain data quality. For statistics on the business sector, in order to reduce burden and costs, we long ago moved away from relying solely on surveys to produce needed estimates, but, to date, we have not done that for household surveys, at least not in the United States. I argue that we can and must move from a paradigm of producing the best estimates possible from a survey to that of producing the best possible estimates to meet user needs from multiple data sources. Such sources include administrative records and, increasingly, transaction and Internet-based data. I provide two examples - household income and plumbing facilities - to illustrate my thesis. I suggest ways to inculcate a culture of official statistics that focuses on the end result of relevant, timely, accurate and cost-effective statistics and treats surveys, along with other data sources, as means to that end.
Release date: 2014-12-19 - Articles and reports: 12-001-X201100211608Description:
Designs and estimators for the single frame surveys currently used by U.S. government agencies were developed in response to practical problems. Federal household surveys now face challenges of decreasing response rates and frame coverage, higher data collection costs, and increasing demand for small area statistics. Multiple frame surveys, in which independent samples are drawn from separate frames, can be used to help meet some of these challenges. Examples include combining a list frame with an area frame or using two frames to sample landline telephone households and cellular telephone households. We review point estimators and weight adjustments that can be used to analyze multiple frame surveys with standard survey software, and summarize construction of replicate weights for variance estimation. Because of their increased complexity, multiple frame surveys face some challenges not found in single frame surveys. We investigate misclassification bias in multiple frame surveys, and propose a method for correcting for this bias when misclassification probabilities are known. Finally, we discuss research that is needed on nonsampling errors with multiple frame surveys.
Release date: 2011-12-21 - Articles 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 - 8. Evaluation of the coverage of linked Canadian Community Health Survey and hospital inpatient records ArchivedArticles and reports: 11-522-X200800010972Description:
Background: Evaluation of the coverage that results from linking routinely collected administrative hospital data with survey data is an important preliminary step to undertaking analyses based on the linked file. Data and methods: To evaluate the coverage of the linkage between data from cycle 1.1 of the Canadian Community Health Survey (CCHS) and in-patient hospital data (Health Person-Oriented Information or HPOI), the number of people admitted to hospital according to HPOI was compared with the weighted estimate for CCHS respondents who were successfully linked to HPOI. Differences between HPOI and the linked and weighted CCHS estimate indicated linkage failure and/or undercoverage. Results: According to HPOI, from September 2000 through November 2001, 1,572,343 people (outside Quebec) aged 12 or older were hospitalized. Weighted estimates from the linked CCHS, adjusted for agreement to link and plausible health number, were 7.7% lower. Coverage rates were similar for males and females. Provincial rates did not differ from those for the rest of Canada, although differences were apparent for the territories. Coverage rates were significantly lower among people aged 75 or older than among those aged 12 to 74.
Release date: 2009-12-03 - Articles and reports: 11-522-X200800010979Description:
Prior to 2006, the Canadian Census of Population relied on field staff to deliver questionnaires to all dwellings in Canada. For the 2006 Census, an address frame was created to cover almost 70% of dwellings in Canada, and these questionnaires were delivered by Canada Post. For the 2011 Census, Statistics Canada aims to expand this frame further, with a target of delivering questionnaires by mail to between 80% and 85% of dwellings. Mailing questionnaires for the Census raises a number of issues, among them: ensuring returned questionnaires are counted in the right area, creating an up to date address frame that includes all new growth, and determining which areas are unsuitable for having questionnaires delivered by mail. Changes to the address frame update procedures for 2011, most notably the decision to use purely administrative data as the frame wherever possible and conduct field update exercises only where deemed necessary, provide a new set of challenges for the 2011 Census.
Release date: 2009-12-03 - 10. Wireless substitution in the U.S. and Canada: prevalence and impact on random-digit-dialed health surveys ArchivedArticles and reports: 11-522-X200600110420Description:
Most major survey research organizations in the United States and Canada do not include wireless telephone numbers when conducting random-digit-dialed (RDD) household telephone surveys. In this paper, we offer the most up-to-date estimates available from the U.S. National Center for Health Statistics and Statistics Canada concerning the prevalence and demographic characteristics of the wireless-only population. We then present data from the U.S. National Health Interview Survey on the health and health care access of wireless-only adults, and we examine the potential for coverage bias when health research is conducted using RDD surveys that exclude wireless telephone numbers.
Release date: 2008-03-17
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Analysis (58)
Analysis (58) (20 to 30 of 58 results)
- Articles and reports: 12-001-X20030026777Description:
The Accuracy and Coverage Evaluation survey was conducted to estimate the coverage in the 2000 U.S. Census. After field procedures were completed, several types of missing data had to be addressed to apply dual-system estimation. Some housing units were not interviewed. Two noninterview adjustments were devised from the same set of interviews, one for each of two points in time. In addition, the resident, match, or enumeration status of some respondents was not determined. Methods applied in the past were replaced to accommodate a tighter schedule to compute and verify the estimates. This paper presents the extent of missing data in the survey, describes the procedures applied, comparing them to past and current alternatives, and provides analytical summaries of the procedures, including comparisons of dual-system estimates of population under alternatives. Because the resulting levels of missing data were low, it appears that alternative procedures would not have affected the results substantially. However some changes in the estimates are noted.
Release date: 2004-01-27 - Articles and reports: 12-001-X20030026780Description:
Coverage errors and other coverage issues related to the population censuses are examined in the light of the recent literature. Especially, when the actual population census count of persons are matched with their corresponding post enumeration survey counts, the aggregated results in a dual record system setting can provide some coverage error statistics.
In this paper, the coverage error issues are evaluated and alternative solutions are discussed in the light of the results from the latest Population Census of Turkey. By using the Census and post enumeration survey data, regional comparison of census coverage was also made and has shown greater variability among regions. Some methodological remarks are also made on the possible improvements on the current enumeration procedures.
Release date: 2004-01-27 - Articles and reports: 12-001-X20020026431Description:
When stand-alone sampling frames that list all establishments and their measures of size are available, establishment surveys typically use the Hansen-Hurwitz (HH) PPS (probability proportional to size) estimator to estimate the volume of transactions that establishments have with populations. This paper proposes the network sampling (NS) version of the HH estimator as a potential competitor of the PPS estimator. The NS estimator depends on the population survey-generated establishment frame that lists households and their selection probabilities in a population sample survey, and the number of transactions, if any, of each household with each establishment. A statistical model is developed in this paper to compare the efficiencies of the HH and NS estimators in single-stage and two-stage establishment sample surveys assuming the stand-alone sampling frame and the population survey-generated frame are flawless in coverage and size measures.
Release date: 2003-01-29 - 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 - 26. Coverage issues in the Canadian Labour Force Survey ArchivedArticles 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 - Articles and reports: 12-001-X20000025531Description:
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 - 30. Census coverage error: A demographic evaluation ArchivedArticles and reports: 12-001-X20000015177Description:
The 1996 Canadian Census is adjusted for coverage error as estimated primarily through the Reverse Record Check (RRC). In this paper, we will show how there is a wealth of additional information from the 1996 Reverse Record Check of direct value to population estimation. Beyond its ability to estimate coverage error, it is possible to extend the Reverse Record Check classification results to obtain an alternative estimate of demographic growth - potentially decomposed by component. This added feature of the Reverse Record Check provides promise in the evaluation of estimated census coverage error as well as insight as to possible problems in the estimation of selected components in the population estimates program.
Release date: 2000-08-30
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