“Optimal” calibration weights under unit nonresponse in survey sampling
Section 4. Concluding remarks

Table of contents

The family of linear calibration techniques in survey sampling contains a variety of alternative weightings under full response, including GREG estimators and the optimal regression estimator. The nonresponse situation offers still more options and challenges and we have studied the “optimal” estimator while also taking into account average response propensities (probabilities). The approach has been design-based since the modified “optimal” estimator can be motivated by asymptotic argumentation and we have furthermore not used any modelling for the response propensities. The results are encouraging, especially concerning reduction of the bias for the suggested estimator. Further work will include the construction of a variance estimator, which should be valid conditionally on the size of the response set.

Acknowledgements

The author is grateful to Carl-Erik Särndal for valuable discussions and suggestions during the research that eventually led to this paper. The author also thanks an anonymous reviewer and an associate editor for helpful comments on the manuscript.

References

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Särndal, C.-E., and Lundström, S. (2005). Estimation in Surveys with Nonresponse. Chichester, UK: Wiley.

Särndal, C.-E., Swensson, B. and Wretman, J. (1992). Model Assisted Survey Sampling. New York: Springer Verlag.

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Table of contents

Abstract - Article main page
Section 1. Introduction
Section 2. Calibration estimation
Section 3. A simulation study
Section 4. Concluding remarks
Acknowledgements
References

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