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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/388

Title: A local influence approach to sensitivity analysis of incomplete longitudinal ordinal data
Authors: Van Steen, Kristel
Molenberghs, Geert
Verbeke, Geert
Thijs, Herbert
Keywords: Categorical data
Longitudinal data
Missing data
Issue Date: 2001
Citation: STATISTICAL MODELLING, 1(2). p. 125-142
Abstract: One of the major concerns when analysing incomplete longitudinal data is the fact that models necessarily rest on strong assumptions, unverifiable from the data. In response to these concerns, there is growing awareness of the usefulness of sensitivity analysis. In this paper we will focus on repeated ordinal data. Specifically, we implement a formal approach to such a sensitivity assessment, based on local influence, in the presence of multivariate categorical data. We explore the influence of perturbing a MAR dropout model in the direction of non-random dropout, and apply the proposed method to data from a longitudinal multicentre psychiatric study.
URI: http://hdl.handle.net/1942/388
DOI: 10.1177/1471082X0100100203
ISSN: 1471-082X
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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