The Causes and Consequences of Response Rates in Surveys by the News Media and Government Contractor Survey Research Firms

Holbrook, Allyson; Krosnick, Jon A.; Pfent, Alison

doi:10.1002/9780470173404.ch23

Cited by 283 publications

(246 citation statements)

References 318 publications

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“…8,9 However, Gallup polls and similar data sets are used regularly to offer timely evaluations of population-level phenomena, including health care-related issues 27,28 and elections. [29][30][31] More importantly, the WBI has been validated against government-conducted surveys for this type of analysis of the uninsured rate, although the same study concluded that the WBI does not reliably measure the type of insurance a person has. 8 In addition, the WBI does not provide information on children's insurance coverage, which may also change under the ACA.…”

Section: Discussionmentioning

confidence: 99%

Health Reform and Changes in Health Insurance Coverage in 2014

et al. 2014

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Section: Discussionmentioning

confidence: 99%

Health Reform and Changes in Health Insurance Coverage in 2014

et al. 2014

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“…Previous research uses status characteristics as indirect proxy measures of isolation to measure and identify marginalized group members. For example, research on general population surveys shows that racial/ethnic minorities, immigrants, people with lower education, and the elderly tend to have lower response rates (Collins et al, 2000;Holbrook et al, 2007;Goyder, 1987;Green, 1996;Groves and Couper, 1998;Smith, 1984;Voogt, 2004). This study focuses on one marginalized status group for our social group isolation hypothesis (gender) and controls for another (race).…”

Section: Marginalized Status and Alternative Explanationsmentioning

confidence: 99%

Social isolation, survey nonresponse, and nonresponse bias: An empirical evaluation using social network data within an organization

Watanabe

Olson

Falci

2017

Social Science Research

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Survey researchers have long hypothesized that social isolation negatively affects the probability of survey participation and biases survey estimates. Previous research, however, has relied on proxy measures of isolation, such as being a marginalized group member within a population. We re-examine the relationship between social isolation and survey participation using direct measures of social isolation derived from social network data; specifically, instrumental research and expressive friendship connections among faculty within academic departments. Using a reconceptualization of social isolation, we find that social network isolation is negatively associated with unit response. Among women (a numerical minority group within the organization), we further find that social group isolation (i.e., lacking instrumental network connections to men, the majority group in the organization) is negatively associated with survey participation. Finally, we show that some survey estimates are systematically biased due to nonparticipation from socially isolated people.

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“…The return rate of questionnaires was, however, very low; only about 11 % of the questionnaires were returned. However, Holbrook, Krosnick, and Pfent (2007) have shown that there is no systematic relationship between response rates and the size of bias encountered in surveys.…”

Section: Settingsmentioning

confidence: 99%