Sensitivity Analysis: Introduction and Overview

Authored by: Molenberghs Geert , Verbeke Geert , G. Kenward Michael

Missing Data Methodology

Print publication date:  November  2014
Online publication date:  November  2014

Print ISBN: 9781439854617
eBook ISBN: 9781439854624
Adobe ISBN:

10.1201/9781439854624-21

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Abstract

It has been seen in Chapters 1 and 3 how, given an MAR missing data mechanism, a valid analysis that ignores the missing value mechanism can be obtained within a likelihood or Bayesian framework, provided that mild regularity conditions hold. For simple non-likelihood-based frequentist inferences, the more stringent MCAR assumption is required. An important class of modified frequentist methods are also valid under MAR however; these include inverse probability weighted and doubly robust semi-parametric approaches (Robins, Rotnitzky, and Zhao 1994, Bang and Robins 2005) (see Chapters 8 and 9). Further, semi-parametric and other frequentist approaches can be combined with multiple imputation to yield inferences that hold under MAR (see Part IV of this volume). An increasing number of software implementations of these methods are now appearing in standard software.

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