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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/9753

Title: Incomplete Data in Clinical Studies: Analysis, Sensitivity, and Sensitivity Analysis
Authors: Molenberghs, Geert
Issue Date: 2009
Citation: DRUG INFORMATION JOURNAL, 43(4). p. 409-429
Abstract: Statistical analysis often extends beyond the data available. This is especially true when data are incompletely recorded because ad hoc as well as model-based approaches are rooted not only in the observed data and the mechanism governing missingness, but also in the unobserved given the observed data. Other instances of this phenomenon include but are not limited to censored time-to-event data, random effects models, and latent class approaches. One needs to be aware of (1) changes in results and intuition relative to complete-data analysis; (2) the assumptions under which such approaches are valid; (3) the sensitivities implied by departures; and (4) in response to these, what sensitivity analysis avenues are available. This article provides a bird's-eye perspective on these. Some of the developments are illustrated using data from a clinical trial in onychomycosis.
Notes: Univ Hasselt, Ctr Stat, B-3590 Diepenbeek, Belgium.
URI: http://hdl.handle.net/1942/9753
ISI #: 000267877500004
ISSN: 0092-8615
Category: A1
Type: Journal Contribution
Validation: ecoom, 2010
Appears in Collections: Research publications

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