Monotone missing data and pattern-mixture models

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

Research output: Contribution to journalArticlepeer-review

101 Scopus citations


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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