Estimator of the Adherer Average Causal Effect

Estimate the causal treatment effect for subjects that can adhere to one or both of the treatments. Given longitudinal data with missing observations, consistent causal effects are calculated. Unobserved potential outcomes are estimated through direct integration as described in: Qu et al., (2019) and Zhang et. al., (2021) .


Reference manual

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install.packages("adace")

1.0.2 by Run Zhuang, 3 years ago


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


Authors: Jiaxun Chen [aut] , Rui Jin [aut] , Yongming Qu [aut] , Run Zhuang [aut, cre] , Ying Zhang [aut] , Eli Lilly and Company [cph]


Documentation:   PDF Manual  


GPL (>= 3) license


Imports reshape2, pracma

Suggests testthat, cubature, MASS


See at CRAN