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http://hdl.handle.net/1942/13001
Title: | Analysis of non-ignorable missing and left-censored longitudinal data using a weighted random effects tobit model | Authors: | Sattar, Abdus Weissfeld, Lisa A. MOLENBERGHS, Geert |
Issue Date: | 2011 | Publisher: | WILEY-BLACKWELL | Source: | STATISTICS IN MEDICINE, 30 (27), p. 3167-3180 | Abstract: | In a longitudinal study with response data collected during a hospital stay, observations may be missing because of the subject's discharge from the hospital prior to completion of the study or the death of the subject, resulting in non-ignorable missing data. In addition to non-ignorable missingness, there is left-censoring in the response measurements because of the inherent limit of detection. For analyzing non-ignorable missing and left-censored longitudinal data, we have proposed to extend the theory of random effects tobit regression model to weighted random effects tobit regression model. The weights are computed on the basis of inverse probability weighted augmented methodology. An extensive simulation study was performed to compare the performance of the proposed model with a number of competitive models. The simulation study shows that the estimates are consistent and that the root mean square errors of the estimates are minimal for the use of augmented inverse probability weights in the random effects tobit model. The proposed method is also applied to the non-ignorable missing and left-censored interleukin-6 biomarker data obtained from the Genetic and Inflammatory Markers of Sepsis study. Copyright (C) 2011 JohnWiley & Sons, Ltd. | Notes: | [Sattar, Abdus] Case Western Reserve Univ, Dept Epidemiol & Biostat, Cleveland, OH 44106 USA. [Weissfeld, Lisa A.] Univ Pittsburgh, Dept Biostat, Pittsburgh, PA 15261 USA. [Molenberghs, Geert] Univ Hasselt, I BioStat, B-3590 Diepenbeek, Belgium. sattar@case.edu | Keywords: | longitudinal data; non-ignorable missing; left-censoring; inverse probability weighting; pseudo-likelihood method;Mathematical & Computational Biology; Public, Environmental & Occupational Health; Medical Informatics; Medicine, Research & Experimental; Statistics & Probability; longitudinal data; non-ignorable missing; left-censoring; inverse probability weighting; pseudo-likelihood method | Document URI: | http://hdl.handle.net/1942/13001 | ISSN: | 0277-6715 | e-ISSN: | 1097-0258 | DOI: | 10.1002/sim.4344 | ISI #: | 000297973100001 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2013 |
Appears in Collections: | Research publications |
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Analysis of non-ignorable missing and left-censored longitudinal data using a weighted random effects tobit model.pdf | Published version | 241.44 kB | Adobe PDF | View/Open |
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