Parametric models for incomplete continuous and categorical longitudinal data
- 1 February 1999
- journal article
- research article
- Published by SAGE Publications in Statistical Methods in Medical Research
- Vol. 8 (1) , 51-83
- https://doi.org/10.1177/096228029900800105
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.Keywords
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