Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/334
Title: | A semi-parametric method of multiple imputation | Authors: | Lipsitz, Stuart R. Zhao, Lue Ping MOLENBERGHS, Geert |
Issue Date: | 1998 | Source: | Journal of the Royal Statistical Society Series B, 60(1). p. 127-144 | 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 URI: | http://hdl.handle.net/1942/334 | ISSN: | 1369-7412 | e-ISSN: | 1467-9868 | DOI: | 10.1111/1467-9868.00113 | ISI #: | 000073377900010 | Rights: | (C) 1998 Royal Statistical Society | Type: | Journal Contribution | Validations: | ecoom 1999 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Lipsitz_et_al-1998-Journal_of_the_Royal_Statistical_Society__Series_B_(Statistical_Methodology).pdf Restricted Access | Published version | 373.36 kB | Adobe PDF | View/Open Request a copy |
SCOPUSTM
Citations
17
checked on Sep 2, 2020
WEB OF SCIENCETM
Citations
25
checked on Sep 11, 2024
Page view(s)
104
checked on Sep 7, 2022
Download(s)
90
checked on Sep 7, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.