Kenward, Michael G. and Molenberghs, G. (1999) Parametric models for incomplete continuous and categorical longitudinal data. Review of: Parametric models for incomplete continuous and categorical longitudinal data. by Kenward, Michael G. and Molenberghs, G.. Statistical Methods in Medical Research, 8 (1). pp. 51-83. ISSN 0962-2802. (doi:10.1191/096228099667825470) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:16888)
| The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
| Official URL: http://smm.sagepub.com/cgi/content/refs/8/1/51 |
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.
| Item Type: | Review |
|---|---|
| DOI/Identification number: | 10.1191/096228099667825470 |
| Subjects: | Q Science |
| Divisions: |
Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science Divisions > Division for the Study of Law, Society and Social Justice > School of Social Policy, Sociology and Social Research |
| Depositing User: | I.T. Ekpo |
| Date Deposited: | 20 Jun 2009 05:20 UTC |
| Last Modified: | 09 Mar 2023 11:31 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/16888 (The current URI for this page, for reference purposes) |
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