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A semiparametric method of multiple imputation

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Abstract:

In this paper, we describe how to use multiple imputation semiparametrically to obtain estimates of parameters and their standard errors when some individuals have missing data. The methods given require the investigator to know or be able to estimate the process generating the missing data but requires no full distributional form for the data. The method is especially useful for non-standard problems, such as estimating the median when data are missing.

Keywords: Complete cases; Missing at random; Missing data mechanism

Document Type: Original Article

DOI: http://dx.doi.org/10.1111/1467-9868.00113

Affiliations: 1: Harvard School of Public Health and Dana Farber Cancer Institute, Boston, USA, 2: Fred Hutchinson Cancer Research Center, Seattle, USA, 3: Limburgs Universitair Centrum, Diepenbeek, Belgium

Publication date: January 1, 1998

bpl/rssb/1998/00000060/00000001/art00010
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