Weighting nonresponse adjustments based on auxiliary information

By Jelke Bethlehem. 2002

190 citations recorded by the source corpus.

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Citations in the corpus

Use of Internet Panels to Conduct Surveys (2015, background): “For instance, bias in the estimate of a simple mean is a function of the covariance between the propensity to respond and the variable of interest, as well as the response propensity of the sample members (Bethlehem, 2002).”
How Much Diversity is Enough? The Curvilinear Relationship Between College Diversity Interactions and First-Year Student Outcomes (2013, result): “Although preliminary analyses showed that the results were similar regardless of whether weighting was used, all analyses were conducted with the weights, which is consistent with the recommendations of survey methodologists and statisticians (e.g., Allison 2002; Bethlehem 2002; Groves et al. 2009; ”
International handbook of survey methodology. (2008, methodology): “For further discussion of the procedures described here and related procedures, see Bethlehem (2002), Gelman and Carlin (2002), and Little & Rubin (2002, Section 3.”
Using proxy measures and other correlates of survey outcomes to adjust for non‐response: examples from multiple surveys (2010, background): “Under a stochastic model for survey non-response (Bethlehem, 2002), the non-response bias of an unadjusted respondent mean y‾ can be expressed as bias(y‾ ) = cov(p, y) (3) p‾ i.e. the covariance between the response probabilities and the survey outcome variable over the average of the response…”
Responsive design for household surveys: tools for actively controlling survey errors and costs (2006, background): “AsBethlehem (2002) has noted, the bias of the unadjusted respondentmean of variable y can be expressed as”
Selection Bias in Web Surveys (2010, unknown): “Bethlehem (1988, 2002) shows that the bias of the sample mean (9) can be written as is the covariance between the values of target variable and the response probabilities in the Internet-population and ¯ ρ is the average response probability.”
Unit Nonresponse and Weighting Adjustments: A Critical Review (2013, background): “may be imposed, such as d * i 1⁄4 divi; where ni is a linear regression estimate (Bethlehem 2002; Särndal and Lundström 2005).”
Proxy Pattern-Mixture Analysis for Survey Nonresponse (2011, background): “probability of response, and bias will vary across items in a single survey (Bethlehem 2002; Groves 2006).”