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A semiparametric method of multiple imputation
Author(s) -
Lipsitz Stuart R.,
Zhao Lue Ping,
Molenberghs Geert
Publication year - 1998
Publication title -
journal of the royal statistical society: series b (statistical methodology)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.523
H-Index - 137
eISSN - 1467-9868
pISSN - 1369-7412
DOI - 10.1111/1467-9868.00113
Subject(s) - missing data , imputation (statistics) , computer science , standard error , econometrics , statistics , data mining , mathematics
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.