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. 2014 Dec;40(2):347-354.
Epub 2014 Dec 19.

Combining information from multiple complex surveys

Qi Dong  1 , Michael R Elliott  2 , Trivellore E Raghunathan  3
Affiliations

Combining information from multiple complex surveys

Qi Dong et al. Surv Methodol. 2014 Dec.

Abstract

This manuscript describes the use of multiple imputation to combine information from multiple surveys of the same underlying population. We use a newly developed method to generate synthetic populations nonparametrically using a finite population Bayesian bootstrap that automatically accounting for complex sample designs. We then analyze each synthetic population with standard complete-data software for simple random samples and obtain valid inference by combining the point and variance estimates using extensions of existing combining rules for synthetic data. We illustrate the approach by combining data from the 2006 National Health Interview Survey (NHIS) and the 2006 Medical Expenditure Panel Survey (MEPS).

Keywords: Bayesian bootstrap; Inverse sampling; Posterior predictive distribution; Synthetic populations.

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References

    1. Cohen MP. Proceedings of the Survey Research Methods Section. American Statistical Association; 1997. The Bayesian bootstrap and multiple imputation for unequal probability sample designs; pp. 635–638.
    1. Dong Q. Unpublished PhD thesis. University of Michigan; 2012.
    1. Dong Q, Elliott MR, Raghunathan TE. A nonparametric method to generate synthetic populations to adjust for complex sampling design features. Survey Methodology. 2014;40(1):29–46. - PMC - PubMed
    1. Elliott MR, Davis WW. Obtaining cancer risk factor prevalence estimates in small areas: combining data from two surveys. Journal of the Royal Statistical Society C: Applied Statistics. 2005;54:595–609.
    1. Ezzati-Rice TM, Rohde F, Greenblatt J. Methodology Report No 22. Agency for Healthcare Research and Quality; Rockville, MD: 2008. [February 2014]. Sample design of the medical expenditure panel survey household component, 1998–2007. Accessed at: http://www.meps.ahrq.gov/mepsweb/data_files/publications/mr22/mr22.pdf.

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