Author(s): Kenward MG, Molenberghs G
Abstract Share this page
Abstract This paper reviews models for incomplete continuous and categorical longitudinal data. In terms of Rubin's classification of missing value processes we are specifically concerned with the problem of nonrandom missingness. A distinction is drawn between the classes of selection and pattern-mixture models and, using several examples, these approaches are compared and contrasted. The central roles of identifiability and sensitivity are emphasized throughout.
This article was published in Stat Methods Med Res
and referenced in Journal of Biometrics & Biostatistics