Abstract – A generalized Heckman model is used for the joint modeling of longitudinal continuous responses and dropout in order to see the influence of a small perturbation of the elements of the covariance structure on displacement of the likelihood. The perturbation from random dropout in the direction of informative dropout is considered for Mastitis data
Incomplete data abound in epidemiological and clinical studies. When the missing data process is not...
To asses the sensitivity of conclusions to model choices in the context of selection models for non-...
There are many methods for analyzing longitudinal ordinal response data with random dropout. These i...
Diggle and Kenward (Appl. Statist. 43 (1994) 49) proposed a selection model for continuous longitudi...
Diggle and Kenward (1994, Applied Statistics 43, 49-93) proposed a selection model for continuous lo...
Diggle and Kenward (1994, Applied Statistics 43, 49-93) proposed a selection model for continuous lo...
The outcome-based selection model of Diggle and Kenward for repeated measurements with non-random dr...
Shared parameter models (SPMs) are a useful approach to addressing bias from informative dropout in ...
One of the major concerns when analysing incomplete longitudinal data is the fact that models necess...
The analysis of longitudinal data with nonignorable dropout remains an active area in biostatistics ...
DIGGLE and KENWARD (1994) proposed a selection model for continuous longitudinal data subject to pos...
In longitudinal studies, subjects may be lost to follow-up and, thus, present incomplete response se...
In longitudinal studies, subjects may be lost to follow up and, thus, present incomplete response se...
This paper considers the impact of bias in the estimation of the association parameters for longitud...
To asses the sensitivity of conclusions to model choices in the context of selection models for non-...
Incomplete data abound in epidemiological and clinical studies. When the missing data process is not...
To asses the sensitivity of conclusions to model choices in the context of selection models for non-...
There are many methods for analyzing longitudinal ordinal response data with random dropout. These i...
Diggle and Kenward (Appl. Statist. 43 (1994) 49) proposed a selection model for continuous longitudi...
Diggle and Kenward (1994, Applied Statistics 43, 49-93) proposed a selection model for continuous lo...
Diggle and Kenward (1994, Applied Statistics 43, 49-93) proposed a selection model for continuous lo...
The outcome-based selection model of Diggle and Kenward for repeated measurements with non-random dr...
Shared parameter models (SPMs) are a useful approach to addressing bias from informative dropout in ...
One of the major concerns when analysing incomplete longitudinal data is the fact that models necess...
The analysis of longitudinal data with nonignorable dropout remains an active area in biostatistics ...
DIGGLE and KENWARD (1994) proposed a selection model for continuous longitudinal data subject to pos...
In longitudinal studies, subjects may be lost to follow-up and, thus, present incomplete response se...
In longitudinal studies, subjects may be lost to follow up and, thus, present incomplete response se...
This paper considers the impact of bias in the estimation of the association parameters for longitud...
To asses the sensitivity of conclusions to model choices in the context of selection models for non-...
Incomplete data abound in epidemiological and clinical studies. When the missing data process is not...
To asses the sensitivity of conclusions to model choices in the context of selection models for non-...
There are many methods for analyzing longitudinal ordinal response data with random dropout. These i...