Nonresponse Rates and Nonresponse Bias in Household Surveys

By R. Groves. 2006

2,576 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Sociology and Political Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/4a37b9be99582bae5ee08075cacf2c2f13439608

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Citations in the corpus

Satisficing Among Reluctant Respondents in a Cross-National Context (2010, background): “While many causes and components of survey quality have been studied in the literature, it is generally accepted that it is total survey error which matters (Biemer and Lyberg 2003; Groves 1989).”
How Social Processes Distort Measurement: The Impact of Survey Nonresponse on Estimates of Volunteer Work in the United States1 (2008, neutral): “nonresponse rates and bias, and a meta-analysis by Groves (2006) shows only a weak”
Assessing the Magnitude of Non-Consent Biases in Linked Survey and Administrative Data (2012, background): “…where the study of nonresponse rates and mechanisms of survey participation dominated the field for a long time before researchers started to systematically assess nonresponse bias (the latter was done in, for example, Schnell (2007); Curtin et al. (2000); Merkle and Edelman (2002); Groves (2006)).”
Mental Health in American Colleges and Universities: Variation Across Student Subgroups and Across Campuses (2013, background): “Sample Weights Given that high survey response rates are increasingly rare (Galea and Tracy, 2007), survey methodologists recommend investigating and adjusting for differences between responders and nonresponders to the extent possible (Groves, 2006).”
Do low survey response rates bias results? Evidence from Japan (2015, background): “…these three variables we make the untestable assumption, which has been a common assumption in the survey research literature (e.g., Curtin, Presser, and Singer 2000, 2005; Groves 2006), that there is a continuum that ranges from more-willing 14 responders to reluctant responders to non-responders.”
Restricting Consumer Credit Access: Household Survey Evidence on Effects around the Oregon Rate Cap (2008, background): “Groves (2006) and Groves and Peytcheva (2008) review this literature; e.g., Groves (2006) examines 30 studies and ‘‘finds that the nonresponse rate, by itself, is a poor predictor of bias magnitudes on the 319 different estimates that can be computed from the studies” (Groves and Peytcheva, 2008, p”
Experiments in Producing Nonresponse Bias (2006, background): “Groves (2006) shows a variety of other causal models involving P and Y that have very different implications.”
Standard survey methods for estimating colony losses and explanatory risk factors in Apis mellifera (2013, background): “In particular, it is good practice to strive for high response rates, although there is no empirical support for the notion that low response rates necessarily produce estimates with high nonresponse bias (Groves, 2006).”
Student Eligibility for a Free Lunch as an SES Measure in Education Research (2010, background): “, wealthier households are less likely to provide income information), truncating the sample and biasing inferences (Groves, 2006).”
Do Child Development Accounts Promote Account Holding, Saving, and Asset Accumulation for Children's Future? Evidence from a Statewide Randomized Experiment. (2013, methodology): “Although a low participation rate does not necessarily generate bias (Groves, 2006), it may raise the issue of Journal of Policy Analysis and Management DOI: 10.1002/pam Published on behalf of the Association for Public Policy Analysis and Management external validity because we cannot fully test…”
Using proxy measures and other correlates of survey outcomes to adjust for non‐response: examples from multiple surveys (2010, background): “The latter criterion has sometimes been neglected in the past, but some common cause of both the survey outcome variables and survey participation is necessary for non-response bias to appear (Groves, 2006).”
Development of origin–destination matrices using mobile phone call data (2014, neutral): “minimize,Z = (V!"#$!% ! − V!"#$%&'() ! )! !!! (3) 311”