Response and nonresponse
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- 61. Is there really any benefit in sending out introductory letters in Random Digit Dialling (RDD) surveys? ArchivedArticles and reports: 11-522-X200800011001Description:
Currently underway, the Québec Population Health Survey (EQSP), for which collection will wrap up in February 2009, provides an opportunity, because of the size of its sample, to assess the impact that sending out introductory letters to respondents has on the response rate in a controlled environment. Since this regional telephone survey is expected to have more than 38,000 respondents, it was possible to use part of its sample for this study without having too great an impact on its overall response rate. In random digit dialling (RDD) surveys such as the EQSP, one of the main challenges in sending out introductory letters is reaching the survey units. Doing so depends largely on our capacity to associate an address with the sample units and on the quality of that information.
This article describes the controlled study proposed by the Institut de la statistique du Québec to measure the effect that sending out introductory letters to respondents had on the survey's response rate.
Release date: 2009-12-03 - Articles and reports: 11-536-X200900110804Description:
This paper deals with calibration estimation for surveys with nonresponse. Efficient weighting adjustment for unit nonresponse requires powerful auxiliary information. The weights in the calibration estimator are computed on information about a specified auxiliary vector. Even with the "best possible" auxiliary vector, some bias remains in the estimator. An indicator of the remaining bias is presented and analyzed.
The many potential auxiliary variables allow the statistician to compose a wide variety of possible auxiliary vectors. The need arises to compare these vectors to assess their effectiveness for bias reduction. To this end we examine an indicator useful for ranking alternative auxiliary vectors in regard to their ability to reduce the bias. The indicator is computed on the auxiliary vector values for the sampled units, responding and nonresponding. An advantage is its independence of the study variables, of which there are many in a large survey.
The properties of the indicator are examined in empirical studies. A synthetic population is constructed and potential auxiliary vectors are ranked with the aid of the indicator. Another empirical illustration illustrates how the indicator is used for selecting auxiliary variables in a large survey at Statistics Sweden.
Release date: 2009-08-11 - Articles and reports: 11-536-X200900110805Description:
The estimation of a finite population distribution function is considered in the presence of nonresponse. An imputation approach is discussed which may also be interpreted as a form of weighted estimation. It is assumed that there are complete measurements on at least one auxiliary variable which is strongly related to the variable of interest. The paper is motivated by an application to the estimation of the distribution of hourly pay using data from the Labour Force Survey in the United Kingdom. In this case the main auxiliary variable is a proxy measure of the variable of interest. Techniques discussed include predictive mean matching, nearest neighbour imputation, fractional imputation and propensity score matching. Some theoretical and numerical properties of alternative procedures will be discussed.
Release date: 2009-08-11 - Articles and reports: 12-001-X200900110887Description:
Many survey organisations focus on the response rate as being the quality indicator for the impact of non-response bias. As a consequence, they implement a variety of measures to reduce non-response or to maintain response at some acceptable level. However, response rates alone are not good indicators of non-response bias. In general, higher response rates do not imply smaller non-response bias. The literature gives many examples of this (e.g., Groves and Peytcheva 2006, Keeter, Miller, Kohut, Groves and Presser 2000, Schouten 2004).
We introduce a number of concepts and an indicator to assess the similarity between the response and the sample of a survey. Such quality indicators, which we call R-indicators, may serve as counterparts to survey response rates and are primarily directed at evaluating the non-response bias. These indicators may facilitate analysis of survey response over time, between various fieldwork strategies or data collection modes. We apply the R-indicators to two practical examples.
Release date: 2009-06-22 - Articles and reports: 12-001-X200800210756Description:
In longitudinal surveys nonresponse often occurs in a pattern that is not monotone. We consider estimation of time-dependent means under the assumption that the nonresponse mechanism is last-value-dependent. Since the last value itself may be missing when nonresponse is nonmonotone, the nonresponse mechanism under consideration is nonignorable. We propose an imputation method by first deriving some regression imputation models according to the nonresponse mechanism and then applying nonparametric regression imputation. We assume that the longitudinal data follow a Markov chain with finite second-order moments. No other assumption is imposed on the joint distribution of longitudinal data and their nonresponse indicators. A bootstrap method is applied for variance estimation. Some simulation results and an example concerning the Current Employment Survey are presented.
Release date: 2008-12-23 - Articles and reports: 75F0002M1992009Description:
There are many issues to consider when developing and conducting a survey. Length, complexity and timing of the survey are all factors that may influence potential respondents' likelihood to participate in a survey. One important issue that affects this decision is the extent to which a questionnaire appears to be an invasion of privacy. Information on income and finances is one type of information that many people are reluctant to share but that is important for policy and research purposes.
Collecting such information for the Survey of Consumer Finances (SCF) has proven difficult, and has resulted in higher than average non-response rate for a supplemental survey to the Labour Force Survey. Given the similarity between the SCF and an upcoming survey, the Survey of Labour and Income Dynamics (SLID), it is important to examine the reasons behind the SCF's higher non-response rate and obtain suggestions for increasing response rate and gaining commitment from respondents to the 6-year SLID.
Statistics Canada asked Price Waterhouse to conduct focus groups and in-depth interviews with respondents and non-respondents to the SCF. The objectives of these focus groups and in-depth interviews were to explore reasons for response and non-response, issues of privacy and confidentiality and understanding of the terms used in the survey, and to test reactions to the appearance of a draft SLID package.
Release date: 2008-10-21 - Articles and reports: 82-003-X200800410704Geography: CanadaDescription:
A 24-hour dietary recall from 16,190 respondents aged 12 or older to the Canadian Community Health Survey - Nutrition was used to determine energy and nutrient intake. To identify plausible respondents, a confidence interval was applied to total energy expenditure derived from equations developed by the Institute of Medicine. Estimates of energy and nutrient intake for plausible respondents were compared with estimates for all respondents.
Release date: 2008-10-15 - 68. Respondent incentives in a multi-mode panel survey: Cumulative effects on nonresponse and bias ArchivedArticles and reports: 12-001-X200800110607Description:
Respondent incentives are increasingly used as a measure of combating falling response rates and resulting risks of nonresponse bias. Nonresponse in panel surveys is particularly problematic, since even low wave-on-wave nonresponse rates can lead to substantial cumulative losses; if nonresponse is differential, this may lead to increasing bias across waves. Although the effects of incentives have been studied extensively in cross-sectional contexts, little is known about cumulative effects across waves of a panel. We provide new evidence about the effects of continued incentive payments on attrition, bias and item nonresponse, using data from a large scale, multi-wave, mixed mode incentive experiment on a UK government panel survey of young people. In this study, incentives significantly reduced attrition, far outweighing negative effects on item response rates in terms of the amount of information collected by the survey per issued case. Incentives had proportionate effects on retention rates across a range of respondent characteristics and as a result did not reduce attrition bias in terms of those characteristics. The effects of incentives on retention rates were larger for unconditional than conditional incentives and larger in postal than telephone mode. Across waves, the effects on attrition decreased somewhat, although the effects on item nonresponse and the lack of effect on bias remained constant. The effects of incentives at later waves appeared to be independent of incentive treatments and mode of data collection at earlier waves.
Release date: 2008-06-26 - 69. Effects of measurement on obesity and morbidity ArchivedArticles and reports: 82-003-X200800210564Geography: CanadaDescription:
This article compares associations between body mass index categories based on self-reported versus measured data with selected health conditions. The goal is to determine if the misclassification resulting from the use of self-reported data alters associations between excess weight and these health conditions. The analysis is based on 2,667 respondents aged 40 or older from the 2005 Canadian Community Health Survey.
Release date: 2008-05-14 - Articles and reports: 82-003-X200800210569Geography: CanadaDescription:
Based on a representative sample of the Canadian population, this article quantifies the bias resulting from the use of self-reported rather than directly measured height, weight and body mass index. The analysis is based on 4,567 respondents to the 2005 Canadian Community Health Survey, who provided self-reported values for height and weight and were then measured.
Release date: 2008-05-14
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Analysis (140)
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- 51. Evaluation and treatment of non-response in the ELFE cohort: Results of the pilot studies ArchivedArticles and reports: 11-522-X200800010960Description:
Non-response is inevitable in any survey, despite all the effort put into reducing it at the various stages of the survey. In particular, non-response can cause bias in the estimates. In addition, non-response is an especially serious problem in longitudinal studies because the sample shrinks over time. France's ELFE (Étude Longitudinale Française depuis l'Enfance) is a project that aims to track 20,000 children from birth to adulthood using a multidisciplinary approach. This paper is based on the results of the initial pilot studies conducted in 2007 to test the survey's feasibility and acceptance. The participation rates are presented (response rate, non-response factors) along with a preliminary description of the non-response treatment methods being considered.
Release date: 2009-12-03 - Articles and reports: 11-522-X200800010975Description:
A major issue in official statistics is the availability of objective measures supporting the based-on-fact decision process. Istat has developed an Information System to assess survey quality. Among other standard quality indicators, nonresponse rates are systematically computed and stored for all surveys. Such a rich information base permits analysis over time and comparisons among surveys. The paper focuses on the analysis of interrelationships between data collection mode and other survey characteristics on total nonresponse. Particular attention is devoted to the extent to which multi-mode data collection improves response rates.
Release date: 2009-12-03 - Articles and reports: 11-522-X200800010976Description:
Many survey organizations use the response rate as an indicator for the quality of survey data. As a consequence, a variety of measures are implemented to reduce non-response or to maintain response at an acceptable level. However, the response rate is not necessarily a good indicator of non-response bias. A higher response rate does not imply smaller non-response bias. What matters is how the composition of the response differs from the composition of the sample as a whole. This paper describes the concept of R-indicators to assess potential differences between the sample and the response. Such indicators may facilitate analysis of survey response over time, between various fieldwork strategies or data collection modes. Some practical examples are given.
Release date: 2009-12-03 - Articles and reports: 11-522-X200800010983Description:
The US Census Bureau conducts monthly, quarterly, and annual surveys of the American economy and a census every 5 years. These programs require significant business effort. New technologies, new forms of organization, and scarce resources affect the ability of businesses to respond. Changes also affect what businesses expect from the Census Bureau, the Census Bureau's internal systems, and the way businesses interact with the Census Bureau.
For several years, the Census Bureau has provided a special relationship to help large companies prepare for the census. We also have worked toward company-centric communication across all programs. A relationship model has emerged that focuses on infrastructure and business practices, and allows the Census Bureau to be more responsive.
This paper focuses on the Census Bureau's company-centric communications and systems. We describe important initiatives and challenges, and we review their impact on Census Bureau practices and respondent behavior.
Release date: 2009-12-03 - Articles and reports: 11-522-X200800010984Description:
The Enterprise Portfolio Manager (EPM) Program at Statistics Canada demonstrated the value of employing a "holistic" approach to managing the relationships we have with our largest and most complex business respondents.
Understanding that different types of respondents should receive different levels of intervention and having learnt the value of employing an "enterprise-centric" approach to managing relationships with important, complex data providers, STC has embraced a response management strategy that divides its business population into four tiers based on size, complexity and importance to survey estimates. Thus segmented, different response management approaches have been developed appropriate to the relative contribution of the segment. This allows STC to target resources to the areas where it stands to achieve the greatest return on investment. Tier I and Tier II have been defined as critical to survey estimates.
Tier I represent the largest, most complex businesses in Canada and is managed through the Enterprise Portfolio Management Program.
Tier II represents businesses that are smaller or less complex than Tier I but still significant in developing accurate measures of the activities of individual industries.
Tier III includes more medium-sized businesses, those that form the bulk of survey samples.
Tier IV represents the smallest businesses which are excluded from collection; for these STC relies entirely on tax information.
The presentation will outline:It works! Results and metrics from the programs that have operationalized the Holistic Response Management strategy.Developing a less subjective, methodological approach to segment the business survey population for HRM. The project team's work to capture the complexity factors intrinsically used by experienced staff to rank respondents. What our so called "problem" respondents have told us about the issues underlying non-response.
Release date: 2009-12-03 - 56. Non-response in a random digit dialling survey: The experience of the General Social Survey's Cycle 21 (2007) ArchivedArticles and reports: 11-522-X200800010994Description:
The growing difficulty of reaching respondents has a general impact on non-response in telephone surveys, especially those that use random digit dialling (RDD), such as the General Social Survey (GSS). The GSS is an annual multipurpose survey with 25,000 respondents. Its aim is to monitor the characteristics of and major changes in Canada's social structure. GSS Cycle 21 (2007) was about the family, social support and retirement. Its target population consisted of persons aged 45 and over living in the 10 Canadian provinces. For more effective coverage, part of the sample was taken from a follow-up with the respondents of GSS Cycle 20 (2006), which was on family transitions. The remainder was a new RDD sample. In this paper, we describe the survey's sampling plan and the random digit dialling method used. Then we discuss the challenges of calculating the non-response rate in an RDD survey that targets a subset of a population, for which the in-scope population must be estimated or modelled. This is done primarily through the use of paradata. The methodology used in GSS Cycle 21 is presented in detail.
Release date: 2009-12-03 - Articles and reports: 11-522-X200800010996Description:
In recent years, the use of paradata has become increasingly important to the management of collection activities at Statistics Canada. Particular attention has been paid to social surveys conducted over the phone, like the Survey of Labour and Income Dynamics (SLID). For recent SLID data collections, the number of call attempts was capped at 40 calls. Investigations of the SLID Blaise Transaction History (BTH) files were undertaken to assess the impact of the cap on calls.The purpose of the first study was to inform decisions as to the capping of call attempts, the second study focused on the nature of nonresponse given the limit of 40 attempts.
The use of paradata as auxiliary information for studying and accounting for survey nonresponse was also examined. Nonresponse adjustment models using different paradata variables gathered at the collection stage were compared to the current models based on available auxiliary information from the Labour Force Survey.
Release date: 2009-12-03 - Articles and reports: 11-522-X200800010999Description:
The choice of number of call attempts in a telephone survey is an important decision. A large number of call attempts makes the data collection costly and time-consuming; and a small number of attempts decreases the response set from which conclusions are drawn and increases the variance. The decision can also have an effect on the nonresponse bias. In this paper we study the effects of number of call attempts on the nonresponse rate and the nonresponse bias in two surveys conducted by Statistics Sweden: The Labour Force Survey (LFS) and Household Finances (HF).
By use of paradata we calculate the response rate as a function of the number of call attempts. To estimate the nonresponse bias we use estimates of some register variables, where observations are available for both respondents and nonrespondents. We also calculate estimates of some real survey parameters as functions of varying number of call attempts. The results indicate that it is possible to reduce the current number of call attempts without getting an increased nonresponse bias.
Release date: 2009-12-03 - Articles and reports: 11-522-X200800011000Description:
The present report reviews the results of a mailing experiment that took place within a large scale demonstration project. A postcard and stickers were sent to a random group of project participants in the period between a contact call and a survey. The researchers hypothesized that, because of the additional mailing (the treatment), the response rates to the upcoming survey would increase. There was, however, no difference between the response rates of the treatment group that received the additional mailing and the control group. In the specific circumstances of the mailing experiment, sending project participants a postcard and stickers as a reminder of the upcoming survey and of their participation in the pilot project was not an efficient way to increase response rates.
Release date: 2009-12-03 - 60. Is there really any benefit in sending out introductory letters in Random Digit Dialling (RDD) surveys? ArchivedArticles and reports: 11-522-X200800011001Description:
Currently underway, the Québec Population Health Survey (EQSP), for which collection will wrap up in February 2009, provides an opportunity, because of the size of its sample, to assess the impact that sending out introductory letters to respondents has on the response rate in a controlled environment. Since this regional telephone survey is expected to have more than 38,000 respondents, it was possible to use part of its sample for this study without having too great an impact on its overall response rate. In random digit dialling (RDD) surveys such as the EQSP, one of the main challenges in sending out introductory letters is reaching the survey units. Doing so depends largely on our capacity to associate an address with the sample units and on the quality of that information.
This article describes the controlled study proposed by the Institut de la statistique du Québec to measure the effect that sending out introductory letters to respondents had on the survey's response rate.
Release date: 2009-12-03
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- Surveys and statistical programs – Documentation: 75-005-M2023001Description: This document provides information on the evolution of response rates for the Labour Force Survey (LFS) and a discussion of the evaluation of two aspects of data quality that ensure the LFS estimates continue providing an accurate portrait of the Canadian labour market.Release date: 2023-10-30
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