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adace (version 1.0.2)

Estimator of the Adherer Average Causal Effect

Description

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) .

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Version

Install

install.packages('adace')

Monthly Downloads

218

Version

1.0.2

License

GPL (>= 3)

Maintainer

Run Zhuang

Last Published

August 28th, 2023

Functions in adace (1.0.2)

est_S_Plus_Plus_MethodA

Estimate the treatment effects for population S_++ using Method A
est_S_Plus_Plus_MethodB

Estimate the treatment effects for population S_++ using Method B
est_S_Star_Plus_MethodB

Estimate the treatment effects for population S_*+ using Method B
est_S_Star_Plus_MethodA

Estimate the treatment effects for population S_*+ using Method A