EconPapers    
Economics at your fingertips  
 

Sensitivity Analysis for Nonrandom Dropout: A Local Influence Approach

Geert Verbeke, Geert Molenberghs, Herbert Thijs, Emmanuel Lesaffre and Michael G. Kenward

Biometrics, 2001, vol. 57, issue 1, 7-14

Abstract: Summary. Diggle and Kenward (1994, Applied Statistics43, 49–93) proposed a selection model for continuous longitudinal data subject to nonrandom dropout. It has provoked a large debate about the role for such models. The original enthusiasm was followed by skepticism about the strong but untestable assumptions on which this type of model invariably rests. Since then, the view has emerged that these models should ideally be made part of a sensitivity analysis. This paper presents a formal and flexible approach to such a sensitivity assessment based on local influence (Cook, 1986, Journal of the Royal Statistical Society, Series B48, 133–169). The influence of perturbing a missing‐at‐random dropout model in the direction of nonrandom dropout is explored. The method is applied to data from a randomized experiment on the inhibition of testosterone production in rats.

Date: 2001
References: View complete reference list from CitEc
Citations: View citations in EconPapers (18) Track citations by RSS feed

Downloads: (external link)
https://doi.org/10.1111/j.0006-341X.2001.00007.x

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:biomet:v:57:y:2001:i:1:p:7-14

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0006-341X

Access Statistics for this article

More articles in Biometrics from The International Biometric Society
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2019-03-13
Handle: RePEc:bla:biomet:v:57:y:2001:i:1:p:7-14