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http://hdl.handle.net/1942/352
Title: | Missing data perspectives of the fluvoxamine data set: a review | Authors: | MOLENBERGHS, Geert GOETGHEBEUR, Els Lipsitz, Stuart Kenward, Michael G. LESAFFRE, Emmanuel MICHIELS, Bart |
Issue Date: | 1999 | Publisher: | JOHN WILEY | Source: | Statistics in Medicine, 18(17-18). p. 2449-2464 | Abstract: | Fitting models to incomplete categorical data requires more care than fitting models to the complete data counterparts, not only in the setting of missing data that are non-randomly missing, but even in the familiar missing at random setting. Various aspects of this point of view have been considered in the literature. We review it using data from a multi-centre trial on the relief of psychiatric symptoms. First, it is shown how the usual expected information matrix (referred to as naive information) is biased even under a missing at random mechanism. Second, issues that arise under non-random missingness assumptions are illustrated. It is argued that at least some of these problems can be avoided using contextual information. | Document URI: | http://hdl.handle.net/1942/352 | DOI: | 10.1002/(SICI)1097-0258(19990915/30)18:17/18<2449::AID-SIM268>3.0.CO;2-W | ISI #: | 000082507800021 | Rights: | Copyright (C) 1999 John Wiley & Sons, Ltd. | Type: | Journal Contribution | Validations: | ecoom 2000 |
Appears in Collections: | Research publications |
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7517.pdf | Published version | 134.95 kB | Adobe PDF | View/Open |
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