Monotone missing data and pattern‐mixture models | Zendy

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

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Monotone missing data and pattern‐mixture models

Author(s) -

Molenberghs G.,

Michiels B.,

Kenward M. G.,

Diggle P. J.

Publication year - 1998

Publication title -

statistica neerlandica

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.52

H-Index - 39

eISSN - 1467-9574

pISSN - 0039-0402

DOI - 10.1111/1467-9574.00075

Subject(s) - missing data , mixture model , monotone polygon , computer science , model selection , selection (genetic algorithm) , mathematics , imputation (statistics) , data mining , artificial intelligence , pattern recognition (psychology) , statistics , geometry

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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