Monotone missing data and pattern-mixture models

G. Molenberghs; B. Michiels; M. G. Kenward; P. J. Diggle

Monotone missing data and pattern-mixture models

G. Molenberghs, B. Michiels, M. G. Kenward, P. J. Diggle

Research output: Contribution to journal › Article › peer-review

Abstract

It is shown that the classical taxonomy of missing data models, namely missing completely at random, missing at random and informative missingness, which has been developed almost exclusively within a selection modelling framework, can also be applied to pattern-mixture models. In particular, intuitively appealing identifying restrictions are proposed for a pattern-mixture MAR mechanism.

Original language	English (US)
Pages (from-to)	153-161
Number of pages	9
Journal	Statistica Neerlandica
Volume	52
Issue number	2
State	Published - Jul 1998
Externally published	Yes

Keywords

Missing at random
Selection model

ASJC Scopus subject areas

Statistics and Probability

Cite this

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title = "Monotone missing data and pattern-mixture models",

abstract = "It is shown that the classical taxonomy of missing data models, namely missing completely at random, missing at random and informative missingness, which has been developed almost exclusively within a selection modelling framework, can also be applied to pattern-mixture models. In particular, intuitively appealing identifying restrictions are proposed for a pattern-mixture MAR mechanism.",

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AU - Michiels, B.

AU - Kenward, M. G.

AU - Diggle, P. J.

PY - 1998/7

Y1 - 1998/7

N2 - It is shown that the classical taxonomy of missing data models, namely missing completely at random, missing at random and informative missingness, which has been developed almost exclusively within a selection modelling framework, can also be applied to pattern-mixture models. In particular, intuitively appealing identifying restrictions are proposed for a pattern-mixture MAR mechanism.

AB - It is shown that the classical taxonomy of missing data models, namely missing completely at random, missing at random and informative missingness, which has been developed almost exclusively within a selection modelling framework, can also be applied to pattern-mixture models. In particular, intuitively appealing identifying restrictions are proposed for a pattern-mixture MAR mechanism.

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KW - Selection model

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Monotone missing data and pattern-mixture models

Abstract

Keywords

ASJC Scopus subject areas

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