Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/1968
Title: | A local influence sensitivity analysis for incomplete longitudinal depression data | Authors: | Shen, Shuyi Y. BEUNCKENS, Caroline Mallinckrodt, Craig MOLENBERGHS, Geert |
Issue Date: | 2006 | Publisher: | TAYLOR & FRANCIS INC | Source: | JOURNAL OF BIOPHARMACEUTICAL STATISTICS, 16(3). p. 365-384 | Abstract: | In the analyses of incomplete longitudinal clinical trial data, there has been a shift, away from simple ad hoc methods that are valid only if the data are missing completely at random (MCAR), to more principled (likelihood-based or Bayesian) ignorable analyses, which are valid under the less restrictive missing at random ( MAR) assumption. The availability of the necessary standard statistical software allows for such analyses in practice. Although the possibility of data missing not at random (MNAR) cannot be ruled out, it is argued that analyses valid under MNAR are not well suited for the primary analysis in clinical trials. Therefore, rather than either forgetting about or blindly shifting to an MNAR framework, the optimal place for MNAR analyses is within a sensitivity analysis context. Such analyses can be used, for example, to assess how sensitive results from an ignorable analysis are to possible departures from MAR and how much results are affected by influential observations. In this article, we apply the local influence sensitivity tool (Verbeke et al., 2001) to a longitudinal depression trial, thereby applying it to continuous outcomes from clinical trials. | Notes: | Hasselt Univ, Ctr Stat, Hasselt, Belgium. Eli Lilly & Co, Indianapolis, IN 46285 USA.Beunckens, C, Hasselt Univ, Ctr Stat, Hasselt, Belgium.caroline.beunckens@uhasselt.be | Keywords: | incomplete clinical trial data; local influence; selection models; sensitivity analysis;incomplete clinical trial data; local influence; selection models; sensitivity analysis | Document URI: | http://hdl.handle.net/1942/1968 | ISSN: | 1054-3406 | e-ISSN: | 1520-5711 | DOI: | 10.1080/10543400600609510 | ISI #: | 000237604900012 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2007 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
shen2006.pdf Restricted Access | Published version | 809.91 kB | Adobe PDF | View/Open Request a copy |
SCOPUSTM
Citations
15
checked on Sep 3, 2020
WEB OF SCIENCETM
Citations
10
checked on Apr 30, 2024
Page view(s)
80
checked on Sep 7, 2022
Download(s)
70
checked on Sep 7, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.