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An index of local sensitivity to nonignorable drop‐out in longitudinal modelling
Author(s) -
Ma Guoguang,
Troxel Andrea B.,
Heitjan Daniel F.
Publication year - 2005
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.2107
Subject(s) - univariate , missing data , multivariate statistics , sensitivity (control systems) , statistics , econometrics , index (typography) , computer science , drop out , neighbourhood (mathematics) , regression analysis , mathematics , mathematical analysis , electronic engineering , world wide web , engineering , economics , demographic economics
In longitudinal studies with potentially nonignorable drop‐out, one can assess the likely effect of the nonignorability in a sensitivity analysis. Troxel et al . proposed a general index of sensitivity to nonignorability , or ISNI, to measure sensitivity of key inferences in a neighbourhood of the ignorable, missing at random (MAR) model. They derived detailed formulas for ISNI in the special case of the generalized linear model with a potentially missing univariate outcome. In this paper, we extend the method to longitudinal modelling. We use a multivariate normal model for the outcomes and a regression model for the drop‐out process, allowing missingness probabilities to depend on an unobserved response. The computation is straightforward, and merely involves estimating a mixed‐effects model and a selection model for the drop‐out, together with some simple arithmetic calculations. We illustrate the method with three examples. Copyright © 2005 John Wiley & Sons, Ltd.