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http://hdl.handle.net/1942/354
Title: | Selection models and pattern-mixture models for incomplete categorical data with covariates | Authors: | MICHIELS, Bart MOLENBERGHS, Geert Lipsitz, Stuart R. |
Issue Date: | 1999 | Publisher: | INTERNATIONAL BIOMETRIC SOC | Source: | Biometrics, 55(3). p. 978-983 | Abstract: | Most models for incomplete data are formulated within the selection model framework. This paper studies similarities and differences of modeling incomplete data within both selection and pattern-mixture settings. The focus is on missing at random mechanisms and on categorical data. Point and interval estimation is discussed. A comparison of both approaches is done on side effects in a psychiatric study. | Keywords: | categorical data; maximum likelihood estimation; missing data; multiple imputation; sensitivity analysis | Document URI: | http://hdl.handle.net/1942/354 | ISSN: | 0006-341X | e-ISSN: | 1541-0420 | DOI: | 10.1111/j.0006-341X.1999.00978.x | ISI #: | 000082683000047 | Type: | Journal Contribution | Validations: | ecoom 2000 |
Appears in Collections: | Research publications |
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Michiels_et_al-1999-Biometrics.pdf Restricted Access | Published version | 552.47 kB | Adobe PDF | View/Open Request a copy |
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