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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/2056

Title: A protective estimator for longitudinal binary data subject to non-ignorable non-monotone missingness
Authors: Fitzmaurice, Garrett M.
Lipsitz, Stuart R.
Molenberghs, Geert
Ibrahim, Joseph G.
Issue Date: 2005
Publisher: BLACKWELL PUBLISHING
Citation: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY, 168. p. 723-735
Abstract: In longitudinal studies missing data are the rule not the exception. We consider the analysis of longitudinal binary data with non-monotone missingness that is thought to be non-ignorable. In this setting a full likelihood approach is complicated algebraically and can be computationally prohibitive when there are many measurement occasions. We propose a 'protective' estimator that assumes that the probability that a response is missing at any occasion depends, in a completely unspecified way, on the value of that variable alone. Relying on this 'protectiveness' assumption, we describe a pseudolikelihood estimator of the regression parameters under non-ignorable missingness, without having to model the missing data mechanism directly. The method proposed is applied to CD4 cell count data from two longitudinal clinical trials of patients infected with the human immunodeficiency virus.
Notes: Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA. Brigham & Womens Hosp, Boston, MA 02115 USA. Med Univ S Carolina, Charleston, SC 29425 USA. Limburgs Univ Centrum, Diepenbeek, Belgium. Univ N Carolina, Chapel Hill, NC 27515 USA.Fitzmaurice, GM, Harvard Univ, Sch Publ Hlth, Dept Biostat, 655 Huntington Ave, Boston, MA 02115 USA.fitzmaur@hsph.harvard.edu
URI: http://hdl.handle.net/1942/2056
DOI: 10.1111/j.1467-985X.2005.00374.x
ISI #: 000232168800006
ISSN: 0964-1998
Category: A1
Type: Journal Contribution
Validation: ecoom, 2006
Appears in Collections: Research publications

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