Estimation in Surveys with Nonresponse

By C. Särndal, Sixten Lundström. 2005

411 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/3f4542feccf388f83002b89ee53dd0aa3b74be26

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In Statistics and Probability

Citations in the corpus

Assessing Auxiliary Vectors for Control of Nonresponse Bias in the Calibration Estimator (2008, methodology): “The indicator Q̂ was introduced on intuitive grounds in Särndal and Lundström (2005), under the notation IND1, and used there to compare different candidate vectors kx in regard to their potential for bias reduction.”
Indicators for the representativeness of survey response (2009, background): “It can be shown (e.g., Bethlehem 1988, Särndal and Lundström 2005) that its bias HTˆ( )B y is approximately equal to HT ( , ) ˆ( ) , C y B y ρ = ρ (14) with 1( , ) 1/ ( ) ( ) N i i iC y N y y=∑ρ = − ρ − ρ the population covariance between the survey items and the response probabilities.”
Using Calibration Weighting to Adjust for Nonresponse Under a Plausible Model (with full appendices) (2007, background): “Särndal & Lundström (2005) also treat the case where the model and benchmark covariates can differ in definition but not in number.”
Survey Estimates by Calibration on Complex Auxiliary Information (2006, methodology): “More generally, the calibration approach to nonresponse treatment is discussed in Deville (2002) and in S̈arndal & Lundstr̈om (2005).”
Bayesian Population Interpolation and Lasso-Based Target Selection in Survey Weighting (2014, neutral): “Notwithstanding some useful guidance available on the subject (e.g., Särndal and Lundstrom, 2005; Bethlehem, Cobben and Schouten, 2011), the complexity of the decision problem means that it is typically addressed with simple, ad hoc methods.”
Selection Bias in Web Surveys (2010, neutral): “An overview of weighting adjustment can be found in Bethlehem (2002) and S¨arndal & Lundstr¨om (2005).”