Displaying 4 results from an estimated 4 matches for "survfitjm".
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2010 Mar 18
0
package JM -- version 0.6-0
...le in mainly two settings. First, when focus is in the
time-to-event outcome and we wish to account for the effect of a
time-dependent covariate measured with error. Second, when focus is in
the longitudinal outcome and we wish to correct for nonrandom dropout.
New features include:
* function survfitJM() has been added that calculates predictions of
subject-specific survival probabilities given a history of longitudinal
responses.
* function dynC() has been added that calculates a dynamic
concordance index for joint models. The function also returns
time-dependent areas under the ROC curv...
2010 Mar 18
0
package JM -- version 0.6-0
...le in mainly two settings. First, when focus is in the
time-to-event outcome and we wish to account for the effect of a
time-dependent covariate measured with error. Second, when focus is in
the longitudinal outcome and we wish to correct for nonrandom dropout.
New features include:
* function survfitJM() has been added that calculates predictions of
subject-specific survival probabilities given a history of longitudinal
responses.
* function dynC() has been added that calculates a dynamic
concordance index for joint models. The function also returns
time-dependent areas under the ROC curv...
2012 Sep 18
0
New Package 'JMbayes' for the Joint Modeling of Longitudinal and Survival Data under a Bayesian approach
...- "shared-RE" where only the random effects of the linear mixed model
are included in the linear predictor of the survival submodel.
The package also provides functionality for computing dynamic
predictions for the longitudinal and time-to-event outcomes using
functions predict() and survfitJM(), respectively.
As always, any kind of feedback (questions, suggestions, bug-reports,
etc.) is more than welcome.
Best,
Dimitris
--
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus University Medical Center
Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands...
2012 Sep 18
0
New Package 'JMbayes' for the Joint Modeling of Longitudinal and Survival Data under a Bayesian approach
...- "shared-RE" where only the random effects of the linear mixed model
are included in the linear predictor of the survival submodel.
The package also provides functionality for computing dynamic
predictions for the longitudinal and time-to-event outcomes using
functions predict() and survfitJM(), respectively.
As always, any kind of feedback (questions, suggestions, bug-reports,
etc.) is more than welcome.
Best,
Dimitris
--
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus University Medical Center
Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands...