Cited by 80Survey Sampling and Estimation TechniquesSurvey Methodology and NonresponseCensus and Population Estimation

Nonresponse weighting adjustment using estimated response probability

Kim, Jae Kwang, Kim, Jay J.·2007·Canadian Journal of Statistics

Abstract

To reduce nonresponse bias in sample surveys, a method of nonresponse weighting adjustment is often used which consists of multiplying the sampling weight of the respondent by the inverse of the estimated response probability. The authors examine the asymptotic properties of this estimator. They prove that it is generally more efficient than an estimator which uses the true response probability, provided that the parameters which govern this probability are estimated by maximum likelihood. The authors discuss variance estimation methods that account for the effect of using the estimated response probability; they compare their performances in a small simulation study. They also discuss extensions to the regression estimator.

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Crossref · 10.1002/cjs.5550350403

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Authors
Kim, J. K., & Kim, J. J.
Affiliations
National Center for Health Statistics (US)
Corresponding author
  • Kim, Jae Kwang
  • Kim, Jay J.
Venue
Canadian Journal of Statistics
Publisher
Wiley
Published
2007-12
Volume
35
Issue
4
Pages
501-514
ISSN
  • 0319-5724 (ISSN-L)
  • 1708-945X
OpenAlex
W2075601854
Cited by
80
References
16
Citations by year
2026: 4 · 2025: 4 · 2024: 2 · 2023: 3 · 2022: 1 · 2021: 7 · 2020: 7 · 2019: 5 · 2018: 4 · 2017: 1 · 2016: 2 · 2015: 5 · 2014: 3 · 2013: 8 · 2012: 9
FWCI
1.58
Type
journal article
Language
en
Open access
closed
Locations
Canadian Journal of Statistics (publishedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Survey Sampling and Estimation Techniques
  • Social Sciences › Sociology and Political Science › Survey Methodology and Nonresponse
  • Physical Sciences › Mathematics › Statistics and Probability › Census and Population Estimation
Keywords
nonresponse bias, asymptotic properties, estimator efficiency, maximum likelihood estimation, variance estimation, regression estimator, sample surveys

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