Parametric models for incomplete continuous and categorical longitudinal data.

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.

journal_name

Stat Methods Med Res

authors

Kenward MG,Molenberghs G

doi

10.1177/096228029900800105

subject

Has Abstract

pub_date

1999-03-01 00:00:00

pages

51-83

issue

1

eissn

0962-2802

issn

1477-0334

journal_volume

8

pub_type

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