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[ML12] Regression modeling of the cumulative incidence function with missing causes of failure using pseudo-observations
Conférences invitées : 58. Biometrisches Kolloquium, March 2012, pp.xx, Berlin,Mots clés: competing risks, missing data
Résumé:
The rationale for the present work is to derive a flexible class of regression models for the the cumulative incidence function when there are missing causes of failure, encompassing key models such as the Fine and Gray and additive (Klein, 2006) models.
More precisely, we propose two approaches that extend the Andersen-Klein approach to the missing cause setting.
The first approach is grounded on the inverse probability weighting
paradigm for dealing with missing data and the second is a multiple imputation method
tailored for the Andersen-Klein model.
We illustrate both approaches by analyzing the data from the ECOG 1178 breast cancer treatment
clinical trial.
Commentaires:
http://www.biometrisches-kolloquium.de/
Equipe:
msdma
Collaboration:
CESP
BibTeX
| @inproceedings { | |||
| ML12, | |||
| title | = | "{Regression modeling of the cumulative incidence function with missing causes of failure using pseudo-observations }", | |
| author | = | " M. Moreno-Betancur and A. Latouche ", | |
| booktitle | = | "{58. Biometrisches Kolloquium}", | |
| year | = | 2012, | |
| month | = | "March", | |
| pages | = | "xx", | |
| address | = | "Berlin, ", | |
| note | = | "{http://www.biometrisches-kolloquium.de/}", | |
| } | |||
