Title: Missing data perspectives of the fluvoxamine data set: a review
Authors: Molenberghs, G ×
Goetghebeur, E J
Lipsitz, S R
Kenward, M G
Lesaffre, Emmanuel
Michiels, B #
Issue Date: 1999
Series Title: Statistics in medicine vol:18 issue:17-18 pages:2449-64
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.
ISSN: 0277-6715
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Leuven Biostatistics and Statistical Bioinformatics Centre (L-BioStat)
× corresponding author
# (joint) last author

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