| Estimating transformations for repeated measures modeling of continuous bounded outcome data. | |
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MedLine Citation:
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PMID: 21240881 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Continuous bounded outcome data are unlikely to meet the usual assumptions for mixed-effects models of normally distributed and independent subject-specific and residual random effects. Additionally, overly complicated model structures might be necessary to account adequately for non-drug (time-dependent) and drug treatment effects. A transformation strategy with a likelihood component for censoring is developed to promote the simplicity of model structures and to improve the plausibility of assumptions on the random effects. The approach is motivated by Health Assessment Questionnaire Disability Index (HAQ-DI) data from a study in subjects with rheumatoid arthritis and is evaluated using a simulation study. Copyright © 2011 John Wiley & Sons, Ltd. |
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Authors:
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Matthew M Hutmacher; Jonathan L French; Sriram Krishnaswami; Sujatha Menon |
Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-1-13 |
Journal Detail:
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Title: Statistics in medicine Volume: - ISSN: 1097-0258 ISO Abbreviation: - Publication Date: 2011 Jan |
Date Detail:
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Created Date: 2011-1-17 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8215016 Medline TA: Stat Med Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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Ann Arbor Pharmacometrics Group (A2PG), 110 E Miller, Garden Suite, Ann Arbor, MI 48104, U.S.A. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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