Monotone missing data and pattern-mixture models

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

Research output: Contribution to journalArticlepeer-review


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 languageEnglish (US)
Pages (from-to)153-161
Number of pages9
JournalStatistica Neerlandica
Issue number2
StatePublished - Jul 1998
Externally publishedYes


  • Missing at random
  • Selection model

ASJC Scopus subject areas

  • Statistics and Probability

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