Geert Molenberghs
University of Hasselt
758 Papers
4.8K Citations
Geert Molenberghs is an academic researcher from University of Hasselt. The author has contributed to research in topics: Missing data & Random effects model. The author has an hindex of 75, co-authored 694 publications. Previous affiliations of Geert Molenberghs include The Catholic University of America & Catholic University of Leuven.
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Papers
Re: A Model to Select Chemotherapy Regimens for Phase III Trials for Extensive-Stage Small-Cell Lung Cancer
Marc Buyse,Pierre Thirion,Robert W. Carlson,Tomasz Burzykowski,Geert Molenberghs,Pascal Piedbois +5 more
TL;DR: The data presented by Chen et al. (1) suggest that the results of phase II trials in SCLC poorly predict the outcomes of patients on phase III trials, and the authors should be cautious in their conclusions.
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Double hierarchical generalized linear models - Discussion
G MacKenzie,David Firth,RA Rigby,DM Stasinopoulos,R Payne,Stephen Senn,WJ Browne,Howard Goldstein,J del Castillo,M Feddag,ID Ha,D. U. Kim,HS Oh,AB Lawson,WW Piegorsch,Geert Molenberghs,Geert Verbeke,Kkw Yau,KM Yu,R Mamon,ZZ Zhang +20 more
- 01 Jan 2006
TL;DR: In this article, the authors present a survey of the state-of-the-art universities in Ireland and the UK, including the following institutions:Universities of Limerick and Limerick University, Ireland, Limerick, Ireland.
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Joint modelling of longitudinal response and time-to-event data using conditional distributions: a Bayesian perspective
TL;DR: A large number of clinical applications and methodological development in the area of joint models of longitudinal and time-to-event outcomes have come up in the last 20 or more years.
Local influence diagnostics for incomplete overdispersed longitudinal counts
TL;DR: This paper developed local influence diagnostics to detect influential subjects when generalized linear mixed models are fitted to incomplete longitudinal overdispersed count data, focusing on the influence stemming from the dropout model specification.
Comparing onset of antidepressant action using a repeated measures approach and a traditional assessment schedule.
Craig H. Mallinckrodt,Michael J. Detke,Christopher Kaiser,John G. Watkin,Geert Molenberghs,Raymond J. Carroll +5 more
TL;DR: The present study assessed the feasibility of comparing onset of action between treatments using a categorical repeated measures approach with a traditional assessment schedule.
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