Handling dropout and clustering in longitudinal multicentre clinical trials

DOI10.1191/1471082X06st113oaOpenAlexW2162813319MaRDI QIDQ4970708

P. del Bianco, Riccardo Borgoni

Publication date: 7 October 2020

Published in: Statistical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1191/1471082x06st113oa

zbMATH Keywords

quality of lifemultilevel modelsHeckman selection modelnot ignorable dropout

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• aML

Cites Work

• Mixture modelling of recurrent event times with long-term survivors: Analysis of Hutterite birth intervals
• Estimation in truncated samples when there is heteroscedasticity
• Semiparametric estimation of censored selection models with a nonparametric selection mechanism
• Finite sample behavior of two step estimators in selection models
• Models for discrete longitudinal data.
• Parameterization of Multivariate Random Effects Models for Categorical Data
• Impact evaluation of job training programmes: Selection bias in multilevel models
• An Investigation of the Robustness of the Tobit Estimator to Non-Normality
• Sample Selection Bias as a Specification Error
• Analysing longitudinal continuous quality of life data with dropout
• Simultaneous analysis of quality of life and survival data
• Proportional hazards models with random effects to examine centre effects in multicentre cancer clinical trials
• Techniques for incorporating longitudinal measurements into analyses of survival data from clinical trials
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