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  • Articles and reports: 11-522-X202200100011
    Description: In 2021, Statistics Canada initiated the Disaggregated Data Action Plan, a multi-year initiative to support more representative data collection methods, enhance statistics on diverse populations to allow for intersectional analyses, and support government and societal efforts to address known inequalities and bring considerations of fairness and inclusion into decision making. As part of this initiative, we are building the Survey Series on People and their Communities, a new probabilistic panel specifically designed to collect data that can be disaggregated according to racialized group. This new tool will allow us to address data gaps and emerging questions related to diversity. This paper will give an overview of the design of the Survey Series on People and their Communities.
    Release date: 2024-03-25

  • Articles and reports: 11-522-X202200100016
    Description: To overcome the traditional drawbacks of chain sampling methods, the sampling method called “network sampling with memory” was developed. Its unique feature is to recreate, gradually in the field, a frame for the target population composed of individuals identified by respondents and to randomly draw future respondents from this frame, thereby minimizing selection bias. Tested for the first time in France between September 2020 and June 2021, for a survey among Chinese immigrants in Île-de-France (ChIPRe), this presentation describes the difficulties encountered during collection—sometimes contextual, due to the pandemic, but mostly inherent to the method.
    Release date: 2024-03-25

  • Articles and reports: 12-001-X202300200014
    Description: Many things have been written about Jean-Claude Deville in tributes from the statistical community (see Tillé, 2022a; Tillé, 2022b; Christine, 2022; Ardilly, 2022; and Matei, 2022) and from the École nationale de la statistique et de l’administration économique (ENSAE) and the Société française de statistique. Pascal Ardilly, David Haziza, Pierre Lavallée and Yves Tillé provide an in-depth look at Jean-Claude Deville’s contributions to survey theory. To pay tribute to him, I would like to discuss Jean-Claude Deville’s contribution to the more day-to-day application of methodology for all the statisticians at the Institut national de la statistique et des études économiques (INSEE) and at the public statistics service. To do this, I will use my work experience, and particularly the four years (1992 to 1996) I spent working with him in the Statistical Methods Unit and the discussions we had thereafter, especially in the 2000s on the rolling census.
    Release date: 2024-01-03

  • Articles and reports: 12-001-X202200100005
    Description:

    Methodological studies of the effects that human interviewers have on the quality of survey data have long been limited by a critical assumption: that interviewers in a given survey are assigned random subsets of the larger overall sample (also known as interpenetrated assignment). Absent this type of study design, estimates of interviewer effects on survey measures of interest may reflect differences between interviewers in the characteristics of their assigned sample members, rather than recruitment or measurement effects specifically introduced by the interviewers. Previous attempts to approximate interpenetrated assignment have typically used regression models to condition on factors that might be related to interviewer assignment. We introduce a new approach for overcoming this lack of interpenetrated assignment when estimating interviewer effects. This approach, which we refer to as the “anchoring” method, leverages correlations between observed variables that are unlikely to be affected by interviewers (“anchors”) and variables that may be prone to interviewer effects to remove components of within-interviewer correlations that lack of interpenetrated assignment may introduce. We consider both frequentist and Bayesian approaches, where the latter can make use of information about interviewer effect variances in previous waves of a study, if available. We evaluate this new methodology empirically using a simulation study, and then illustrate its application using real survey data from the Behavioral Risk Factor Surveillance System (BRFSS), where interviewer IDs are provided on public-use data files. While our proposed method shares some of the limitations of the traditional approach – namely the need for variables associated with the outcome of interest that are also free of measurement error – it avoids the need for conditional inference and thus has improved inferential qualities when the focus is on marginal estimates, and it shows evidence of further reducing overestimation of larger interviewer effects relative to the traditional approach.

    Release date: 2022-06-21

  • Articles and reports: 11-522-X202100100007
    Description: The National Center for Health Statistics (NCHS) annually administers the National Ambulatory Medical Care Survey (NAMCS) to assess practice characteristics and ambulatory care provided by office-based physicians in the United States, including interviews with sampled physicians. After the onset of the COVID-19 pandemic, NCHS adapted NAMCS methodology to assess the impacts of COVID-19 on office-based physicians, including: shortages of personal protective equipment; COVID-19 testing in physician offices; providers testing positive for COVID-19; and telemedicine use during the pandemic. This paper describes challenges and opportunities in administering the 2020 NAMCS and presents key findings regarding physician experiences during the COVID-19 pandemic.

    Key Words: National Ambulatory Medical Care Survey (NAMCS); Office-based physicians; Telemedicine; Personal protective equipment.

    Release date: 2021-10-22

  • Articles and reports: 12-001-X202100100006
    Description:

    It is now possible to manage surveys using statistical models and other tools that can be applied in real time. This paper focuses on three developments that reflect the attempt to take a more scientific approach to the management of survey field work: 1) the use of responsive and adaptive designs to reduce nonresponse bias, other sources of error, or costs; 2) optimal routing of interviewer travel to reduce costs; and 3) rapid feedback to interviewers to reduce measurement error. The article begins by reviewing experiments and simulation studies examining the effectiveness of responsive and adaptive designs. These studies suggest that these designs can produce modest gains in the representativeness of survey samples or modest cost savings, but can also backfire. The next section of the paper examines efforts to provide interviewers with a recommended route for their next trip to the field. The aim is to bring interviewers’ field work into closer alignment with research priorities while reducing travel time. However, a study testing this strategy found that interviewers often ignore such instructions. Then, the paper describes attempts to give rapid feedback to interviewers, based on automated recordings of their interviews. Interviewers often read questions in ways that affect respondents’ answers; correcting these problems quickly yielded marked improvements in data quality. All of the methods are efforts to replace the judgment of interviewers, field supervisors, and survey managers with statistical models and scientific findings.

    Release date: 2021-06-24

  • Articles and reports: 62F0014M2020016
    Description:

    A summary of methodological treatments as applied to the August 2020 CPI in response to the effects of the COVID-19 pandemic on price collection, price availability, and business closures.

    Release date: 2020-09-16

  • Articles and reports: 82-003-X202000800002
    Description:

    The purpose of this study was to examine the psychometric properties of the parent-rated Strengths and Difficulties Questionnaire with a nationally representative sample of Canadian children and adolescents.

    Release date: 2020-08-19

  • Articles and reports: 12-001-X201900200009
    Description:

    In recent years, there has been a strong interest in indirect measures of nonresponse bias in surveys or other forms of data collection. This interest originates from gradually decreasing propensities to respond to surveys parallel to pressures on survey budgets. These developments led to a growing focus on the representativeness or balance of the responding sample units with respect to relevant auxiliary variables. One example of a measure is the representativeness indicator, or R-indicator. The R-indicator is based on the design-weighted sample variation of estimated response propensities. It pre-supposes linked auxiliary data. One of the criticisms of the indicator is that it cannot be used in settings where auxiliary information is available only at the population level. In this paper, we propose a new method for estimating response propensities that does not need auxiliary information for non-respondents to the survey and is based on population auxiliary information. These population-based response propensities can then be used to develop R-indicators that employ population contingency tables or population frequency counts. We discuss the statistical properties of the indicators, and evaluate their performance using an evaluation study based on real census data and an application from the Dutch Health Survey.

    Release date: 2019-06-27

  • Articles and reports: 12-001-X201800254957
    Description:

    When a linear imputation method is used to correct non-response based on certain assumptions, total variance can be assigned to non-responding units. Linear imputation is not as limited as it seems, given that the most common methods – ratio, donor, mean and auxiliary value imputation – are all linear imputation methods. We will discuss the inference framework and the unit-level decomposition of variance due to non-response. Simulation results will also be presented. This decomposition can be used to prioritize non-response follow-up or manual corrections, or simply to guide data analysis.

    Release date: 2018-12-20
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Analysis (222)

Analysis (222) (0 to 10 of 222 results)

  • Articles and reports: 11-522-X202200100011
    Description: In 2021, Statistics Canada initiated the Disaggregated Data Action Plan, a multi-year initiative to support more representative data collection methods, enhance statistics on diverse populations to allow for intersectional analyses, and support government and societal efforts to address known inequalities and bring considerations of fairness and inclusion into decision making. As part of this initiative, we are building the Survey Series on People and their Communities, a new probabilistic panel specifically designed to collect data that can be disaggregated according to racialized group. This new tool will allow us to address data gaps and emerging questions related to diversity. This paper will give an overview of the design of the Survey Series on People and their Communities.
    Release date: 2024-03-25

  • Articles and reports: 11-522-X202200100016
    Description: To overcome the traditional drawbacks of chain sampling methods, the sampling method called “network sampling with memory” was developed. Its unique feature is to recreate, gradually in the field, a frame for the target population composed of individuals identified by respondents and to randomly draw future respondents from this frame, thereby minimizing selection bias. Tested for the first time in France between September 2020 and June 2021, for a survey among Chinese immigrants in Île-de-France (ChIPRe), this presentation describes the difficulties encountered during collection—sometimes contextual, due to the pandemic, but mostly inherent to the method.
    Release date: 2024-03-25

  • Articles and reports: 12-001-X202300200014
    Description: Many things have been written about Jean-Claude Deville in tributes from the statistical community (see Tillé, 2022a; Tillé, 2022b; Christine, 2022; Ardilly, 2022; and Matei, 2022) and from the École nationale de la statistique et de l’administration économique (ENSAE) and the Société française de statistique. Pascal Ardilly, David Haziza, Pierre Lavallée and Yves Tillé provide an in-depth look at Jean-Claude Deville’s contributions to survey theory. To pay tribute to him, I would like to discuss Jean-Claude Deville’s contribution to the more day-to-day application of methodology for all the statisticians at the Institut national de la statistique et des études économiques (INSEE) and at the public statistics service. To do this, I will use my work experience, and particularly the four years (1992 to 1996) I spent working with him in the Statistical Methods Unit and the discussions we had thereafter, especially in the 2000s on the rolling census.
    Release date: 2024-01-03

  • Articles and reports: 12-001-X202200100005
    Description:

    Methodological studies of the effects that human interviewers have on the quality of survey data have long been limited by a critical assumption: that interviewers in a given survey are assigned random subsets of the larger overall sample (also known as interpenetrated assignment). Absent this type of study design, estimates of interviewer effects on survey measures of interest may reflect differences between interviewers in the characteristics of their assigned sample members, rather than recruitment or measurement effects specifically introduced by the interviewers. Previous attempts to approximate interpenetrated assignment have typically used regression models to condition on factors that might be related to interviewer assignment. We introduce a new approach for overcoming this lack of interpenetrated assignment when estimating interviewer effects. This approach, which we refer to as the “anchoring” method, leverages correlations between observed variables that are unlikely to be affected by interviewers (“anchors”) and variables that may be prone to interviewer effects to remove components of within-interviewer correlations that lack of interpenetrated assignment may introduce. We consider both frequentist and Bayesian approaches, where the latter can make use of information about interviewer effect variances in previous waves of a study, if available. We evaluate this new methodology empirically using a simulation study, and then illustrate its application using real survey data from the Behavioral Risk Factor Surveillance System (BRFSS), where interviewer IDs are provided on public-use data files. While our proposed method shares some of the limitations of the traditional approach – namely the need for variables associated with the outcome of interest that are also free of measurement error – it avoids the need for conditional inference and thus has improved inferential qualities when the focus is on marginal estimates, and it shows evidence of further reducing overestimation of larger interviewer effects relative to the traditional approach.

    Release date: 2022-06-21

  • Articles and reports: 11-522-X202100100007
    Description: The National Center for Health Statistics (NCHS) annually administers the National Ambulatory Medical Care Survey (NAMCS) to assess practice characteristics and ambulatory care provided by office-based physicians in the United States, including interviews with sampled physicians. After the onset of the COVID-19 pandemic, NCHS adapted NAMCS methodology to assess the impacts of COVID-19 on office-based physicians, including: shortages of personal protective equipment; COVID-19 testing in physician offices; providers testing positive for COVID-19; and telemedicine use during the pandemic. This paper describes challenges and opportunities in administering the 2020 NAMCS and presents key findings regarding physician experiences during the COVID-19 pandemic.

    Key Words: National Ambulatory Medical Care Survey (NAMCS); Office-based physicians; Telemedicine; Personal protective equipment.

    Release date: 2021-10-22

  • Articles and reports: 12-001-X202100100006
    Description:

    It is now possible to manage surveys using statistical models and other tools that can be applied in real time. This paper focuses on three developments that reflect the attempt to take a more scientific approach to the management of survey field work: 1) the use of responsive and adaptive designs to reduce nonresponse bias, other sources of error, or costs; 2) optimal routing of interviewer travel to reduce costs; and 3) rapid feedback to interviewers to reduce measurement error. The article begins by reviewing experiments and simulation studies examining the effectiveness of responsive and adaptive designs. These studies suggest that these designs can produce modest gains in the representativeness of survey samples or modest cost savings, but can also backfire. The next section of the paper examines efforts to provide interviewers with a recommended route for their next trip to the field. The aim is to bring interviewers’ field work into closer alignment with research priorities while reducing travel time. However, a study testing this strategy found that interviewers often ignore such instructions. Then, the paper describes attempts to give rapid feedback to interviewers, based on automated recordings of their interviews. Interviewers often read questions in ways that affect respondents’ answers; correcting these problems quickly yielded marked improvements in data quality. All of the methods are efforts to replace the judgment of interviewers, field supervisors, and survey managers with statistical models and scientific findings.

    Release date: 2021-06-24

  • Articles and reports: 62F0014M2020016
    Description:

    A summary of methodological treatments as applied to the August 2020 CPI in response to the effects of the COVID-19 pandemic on price collection, price availability, and business closures.

    Release date: 2020-09-16

  • Articles and reports: 82-003-X202000800002
    Description:

    The purpose of this study was to examine the psychometric properties of the parent-rated Strengths and Difficulties Questionnaire with a nationally representative sample of Canadian children and adolescents.

    Release date: 2020-08-19

  • Articles and reports: 12-001-X201900200009
    Description:

    In recent years, there has been a strong interest in indirect measures of nonresponse bias in surveys or other forms of data collection. This interest originates from gradually decreasing propensities to respond to surveys parallel to pressures on survey budgets. These developments led to a growing focus on the representativeness or balance of the responding sample units with respect to relevant auxiliary variables. One example of a measure is the representativeness indicator, or R-indicator. The R-indicator is based on the design-weighted sample variation of estimated response propensities. It pre-supposes linked auxiliary data. One of the criticisms of the indicator is that it cannot be used in settings where auxiliary information is available only at the population level. In this paper, we propose a new method for estimating response propensities that does not need auxiliary information for non-respondents to the survey and is based on population auxiliary information. These population-based response propensities can then be used to develop R-indicators that employ population contingency tables or population frequency counts. We discuss the statistical properties of the indicators, and evaluate their performance using an evaluation study based on real census data and an application from the Dutch Health Survey.

    Release date: 2019-06-27

  • Articles and reports: 12-001-X201800254957
    Description:

    When a linear imputation method is used to correct non-response based on certain assumptions, total variance can be assigned to non-responding units. Linear imputation is not as limited as it seems, given that the most common methods – ratio, donor, mean and auxiliary value imputation – are all linear imputation methods. We will discuss the inference framework and the unit-level decomposition of variance due to non-response. Simulation results will also be presented. This decomposition can be used to prioritize non-response follow-up or manual corrections, or simply to guide data analysis.

    Release date: 2018-12-20
Reference (1)

Reference (1) ((1 result))

  • Surveys and statistical programs – Documentation: 75F0002M1992001
    Description:

    Starting in 1994, the Survey of Labour and Income Dynamics (SLID) will follow individuals and families for at least six years, tracking their labour market experiences, changes in income and family circumstances. An initial proposal for the content of SLID, entitled "Content of the Survey of Labour and Income Dynamics : Discussion Paper", was distributed in February 1992.

    That paper served as a background document for consultation with and a review by interested users. The content underwent significant change during this process. Based upon the revised content, a large-scale test of SLID will be conducted in February and May 1993.

    The present document outlines the income and wealth content to be tested in May 1993. This document is really a continuation of SLID Research Paper Series 92-01A, which outlines the demographic and labour content used in the January /February 1993 test.

    Release date: 2008-02-29
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