Prediction of Therapeutic Success

In personalized medicine, one wants to know, for a given patient and his or her outcome for a predictor (pre-treatment variable), how likely it is that a treatment will be more beneficial than an alternative treatment. This package allows for the quantification of the predictive causal association (i.e., the association between the predictor variable and the individual causal effect of the treatment) and related metrics. Part of this software has been developed using funding provided from the European Union's 7th Framework Programme for research, technological development and demonstration under Grant Agreement no 602552.


Reference manual

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install.packages("EffectTreat")

1.1 by Wim Van der Elst, 6 years ago


Browse source code at https://github.com/cran/EffectTreat


Authors: Wim Van der Elst , Ariel Alonso & Geert Molenberghs


Documentation:   PDF Manual  


GPL (>= 2) license


Imports methods


See at CRAN