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Household Surveys in Crisis
Household surveys, one of the main innovations in social science research of the last century, are threatened by declining accuracy due to reduced cooperation of respondents. While many indicators of survey quality have steadily declined in recent decades, the literature has largely emphasized rising nonresponse rates rather than other potentially more important dimensions to the problem. We divide the problem into rising rates of nonresponse, imputation, and measurement error, documenting the rise in each of these threats to survey quality over the past three decades. A fundamental problem in assessing biases due to these problems in surveys is the lack of a benchmark or measure of truth, leading us to focus on the accuracy of the reporting of government transfers. We provide evidence from aggregate measures of transfer reporting as well as linked microdata. We discuss the relative importance of misreporting of program receipt and conditional amounts of benefits received, as well as some of the conjectured reasons for declining cooperation and for survey errors. We end by discussing ways to reduce the impact of the problem including the increased use of administrative data and the possibilities for combining administrative and survey data.
Journal Article
Where Do We Go from Here? Nonresponse and Social Measurement
Surveys undergird government statistical systems and social scientific research throughout the world. Rates of nonresponse are rising in cross-sectional surveys (those conducted during a fixed period of time and not repeated). Although this trend worries those concerned with the validity of survey data, there is no necessary relationship between the rate of nonresponse and the degree of bias. A high rate of nonresponse merely creates the potential for bias, but the degree of bias depends on how factors promoting nonresponse are related to variables of interest. Nonresponse can be reduced by offering financial incentives to respondents and by careful design before entering the field, creating a trade-off between cost and potential bias. When bias is suspected, it can be countered by weighting individual cases by the inverse of their response propensity. Response propensities are typically estimated using a logistic regression equation to predict the dichotomous outcome of survey participation as a function of auxiliary variables. The Multi-level Integrated Database Approach employs multiple databases to collect as much information as possible about the target sample during the initial sampling stage and at all possible levels of aggregation to maximize the accuracy of estimated response propensities.
Journal Article
A randomised trial and economic evaluation of the effect of response mode on response rate, response bias, and item non-response in a survey of doctors
Background
Surveys of doctors are an important data collection method in health services research. Ways to improve response rates, minimise survey response bias and item non-response, within a given budget, have not previously been addressed in the same study. The aim of this paper is to compare the effects and costs of three different modes of survey administration in a national survey of doctors.
Methods
A stratified random sample of 4.9% (2,702/54,160) of doctors undertaking clinical practice was drawn from a national directory of all doctors in Australia. Stratification was by four doctor types: general practitioners, specialists, specialists-in-training, and hospital non-specialists, and by six rural/remote categories. A three-arm parallel trial design with equal randomisation across arms was used. Doctors were randomly allocated to: online questionnaire (902); simultaneous mixed mode (a paper questionnaire and login details sent together) (900); or, sequential mixed mode (online followed by a paper questionnaire with the reminder) (900). Analysis was by intention to treat, as within each primary mode, doctors could choose either paper or online. Primary outcome measures were response rate, survey response bias, item non-response, and cost.
Results
The online mode had a response rate 12.95%, followed by the simultaneous mixed mode with 19.7%, and the sequential mixed mode with 20.7%. After adjusting for observed differences between the groups, the online mode had a 7 percentage point lower response rate compared to the simultaneous mixed mode, and a 7.7 percentage point lower response rate compared to sequential mixed mode. The difference in response rate between the sequential and simultaneous modes was not statistically significant. Both mixed modes showed evidence of response bias, whilst the characteristics of online respondents were similar to the population. However, the online mode had a higher rate of item non-response compared to both mixed modes. The total cost of the online survey was 38% lower than simultaneous mixed mode and 22% lower than sequential mixed mode. The cost of the sequential mixed mode was 14% lower than simultaneous mixed mode. Compared to the online mode, the sequential mixed mode was the most cost-effective, although exhibiting some evidence of response bias.
Conclusions
Decisions on which survey mode to use depend on response rates, response bias, item non-response and costs. The sequential mixed mode appears to be the most cost-effective mode of survey administration for surveys of the population of doctors, if one is prepared to accept a degree of response bias. Online surveys are not yet suitable to be used exclusively for surveys of the doctor population.
Journal Article
Nonresponse in Social Science Surveys
For many household surveys in the United States, responses rates have been steadily declining for at least the past two decades. A similar decline in survey response can be observed in all wealthy countries. Efforts to raise response rates have used such strategies as monetary incentives or repeated attempts to contact sample members and obtain completed interviews, but these strategies increase the costs of surveys. This review addresses the core issues regarding survey nonresponse. It considers why response rates are declining and what that means for the accuracy of survey results. These trends are of particular concern for the social science community, which is heavily invested in obtaining information from household surveys. The evidence to date makes it apparent that current trends in nonresponse, if not arrested, threaten to undermine the potential of household surveys to elicit information that assists in understanding social and economic issues. The trends also threaten to weaken the validity of inferences drawn from estimates based on those surveys. High nonresponse rates create the potential or risk for bias in estimates and affect survey design, data collection, estimation, and analysis.
The survey community is painfully aware of these trends and has responded aggressively to these threats. The interview modes employed by surveys in the public and private sectors have proliferated as new technologies and methods have emerged and matured. To the traditional trio of mail, telephone, and face-to-face surveys have been added interactive voice response (IVR), audio computer-assisted self-interviewing (ACASI), web surveys, and a number of hybrid methods. Similarly, a growing research agenda has emerged in the past decade or so focused on seeking solutions to various aspects of the problem of survey nonresponse; the potential solutions that have been considered range from better training and deployment of interviewers to more use of incentives, better use of the information collected in the data collection, and increased use of auxiliary information from other sources in survey design and data collection. Nonresponse in Social Science Surveys: A Research Agenda also documents the increased use of information collected in the survey process in nonresponse adjustment.
eBook
Survey administration and participation: a randomized trial in a panel population health survey
Background
Choice of survey administration features in surveys mapping population health may influence the participation and the generalizability of the results. This randomized study aimed to investigate whether three digital letters (denoted single-mode administration) lead to similar participation as two digital and three physical letters mailed with shorter duration between reminders (denoted sequential mixed-mode administration).
Methods
In total, 9,489 individuals who participated in The Danish Capital Region Health Survey in 2017 were randomized to re-invitation in 2021 (≥ 20 years) by either single-mode with three digital letters (N = 4,745) or sequential mixed-mode survey administration with two digital and then three physical letters (N = 4,744). To investigate the influence of survey administration on representativeness, the two groups were compared regarding sociodemographic characteristics of participants (age, sex, country of origin, education, labor market attachment). Generalized linear models were used to estimate absolute and relative differences between the two administration groups in participation rates (overall and the increase after reminders). It was also investigated whether sociodemographic factors moderated the association between administration group and participation.
Results
At the end of follow-up, the participation rate was significantly higher in the sequential mixed-mode group, which received five letters (78%), than in the single-mode group, which received three letters (61%), primarily due to a greater increase in participation after switching to physical administration and an increase after the two additional reminders in the mixed-mode group. Overall, individuals who decided to participate in the two groups were comparable in all sociodemographic factors, yet older participants appeared to benefit more from switching to physical administration and younger participants from additional reminders.
Conclusions
Depending on the target population, sequential mixed-mode survey administration and/or multiple reminders could be considered to increase participation; however, it does not necessarily improve the sociodemographic representativeness of participants.
Journal Article