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http://hdl.handle.net/1942/10769
Title: | Missing data methods in longitudinal studies: a review | Authors: | IBRAHIM, Joseph MOLENBERGHS, Geert |
Issue Date: | 2009 | Publisher: | SPRINGER | Source: | TEST, 18(1). p. 1-43 | Abstract: | Incomplete data are quite common in biomedical and other types of research, especially in longitudinal studies. During the last three decades, a vast amount of work has been done in the area. This has led, on the one hand, to a rich taxonomy of missing-data concepts, issues, and methods and, on the other hand, to a variety of data-analytic tools. Elements of taxonomy include: missing data patterns, mechanisms, and modeling frameworks; inferential paradigms; and sensitivity analysis frameworks. These are described in detail. A variety of concrete modeling devices is presented. To make matters concrete, two case studies are considered. The first one concerns quality of life among breast cancer patients, while the second one examines data from the Muscatine children's obesity study. | Notes: | [Ibrahim, Joseph G.] Univ N Carolina, Dept Biostat, Chapel Hill, NC 27515 USA. [Molenberghs, Geert] Hasselt Univ, Ctr Stat, Int Inst Biostat & Stat Bioinformat, B-3590 Diepenbeek, Belgium. [Molenberghs, Geert] Catholic Univ Leuven, B-3590 Diepenbeek, Belgium. | Keywords: | expectation-maximization algorithm; incomplete data; missing completely at random; missing at random; missing not at random; pattern-mixture model; selection model; sensitivity analyses; shared-parameter model;Expectation-maximization algorithm; Incomplete data; Missing completely at random; Missing at random; Missing not at random; Pattern-mixture model; Selection model; Sensitivity analyses; Shared-parameter model | Document URI: | http://hdl.handle.net/1942/10769 | ISSN: | 1133-0686 | e-ISSN: | 1863-8260 | DOI: | 10.1007/s11749-009-0138-x | ISI #: | 000264549700001 | Rights: | © Sociedad de Estadística e Investigación Operativa 2009 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2010 |
Appears in Collections: | Research publications |
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Invited_paper_Ibrahim_Molenberghs_feb_2009.pdf | Peer-reviewed author version | 246 kB | Adobe PDF | View/Open |
a.pdf Restricted Access | Published version | 651.17 kB | Adobe PDF | View/Open Request a copy |
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