Disclosure Limitation

Disclosure Avoidance

Disclosure avoidance is an important concern in survey research, and I have been interested in the use of multiple imputation to reduce the risk of disclosure. An early paper discussing different forms of multiple imputation and other approaches is Little (1993). Subsequent research includes Liu & Little (2002, 2003), Little, Liu & Raghunathan (2004), An & Little (2007), and An, Little & McNally (2010

References

An, D. & Little, R.J. (2007). Multiple Imputation: an Alternative to Top-Coding for Statistical Disclosure Control. Journal of the Royal Statistical Society, Ser. A, 170, 4, 923-940. {15}

An, D., Little, R.J. & McNally, J. (2010). A Multiple Imputation Approach to Disclosure Limitation for High-Age Individuals in Longitudinal Studies. Statistics in Medicine, 29, 17, 1769-1778.

Little, R.J.A. (1993). Statistical Analysis of Masked Data. Journal of Official Statistics 9, 407-426.

Little, R.J., Liu, F. & Raghunathan, T. (2004). Statistical Disclosure Techniques Based on Multiple Imputation. In “Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives”, A. Gelman & X.-L. Meng, eds., pp. 141-152. Wiley: New York. {18}

Liu, F. & Little, R.J.A. (2002). Multiple Imputation and Statistical Disclosure Control in Microdata. Proceedings of the Survey Research Methods Section, American Statistical Association 2002, 2133-2138.

Liu, F. & Little, R.J.A. (2003). Smike vs. Data Swapping and PRAM for Statistical Disclosure Control in Microdata: a Simulated Study. Proceedings of the Survey Research Methods Section, American Statistical Association 2003, 2497-2502.

(revised December 8, 2011)