ATOPobs | R Documentation |
This function computes the bounds on the average treatment effect among always-observed pairs (ATOP) with pre-specified sensivity parameters when some of the outcome data are missing. The sensivity parameters characterizes the degree of the within-pair similarity and the dependence between the potential missing indicators and the treatment. The confidence intervals for the ATOP are also computed.
ATOPobs(Ya, Yb, Ra, Rb, Ta, Tb, gamma, kappa1, kappa0, l, u, alpha, rep)
Ya |
A vector of the outcomes of the first unit in the matched pairs. The missing values for |
Yb |
A vector of the outcomes of the second unit in the matched pairs. The missing values for |
Ra |
A vector of the missing data indicators of the first unit in the matched pairs. |
Rb |
A vector of the missing data indicators of the second unit in the matched pairs. |
Ta |
A vector of the treatment conditions of the first unit in the matched pairs. |
Tb |
A vector of the treatment conditions of the second unit in the matched pairs. |
gamma |
The sensitivity parameter which charaterizes the degree of the within-pair similarity. |
kappa1 |
The sensitivity parameter which charaterizes the dependence between |
kappa0 |
The sensitivity parameter which charaterizes the dependence between |
l |
The lower limit of the outcome. |
u |
The upper limit of the outcome. |
alpha |
A positive scalar that is less than or equal to 0.5. This will
determine the (1- |
rep |
The number of repetitions for bootstraping. |
For the details of the method implemented by this function, see the references.
A list of class ATOPsens
which contains the following items:
LB |
The lower bound for the ATOP. |
UB |
The upper bound for the ATOP. |
LB.CI |
The lower limit of the confidence interval for the ATOP. |
UB.CI |
The upper limit of the confidence interval for the ATOP. |
Kosuke Imai, Department of Government and Department of Statistics, Harvard University imai@Harvard.Edu, https://imai.fas.harvard.edu; Zhichao Jiang, Department of Politics, Princeton University zhichaoj@princeton.edu.
Kosuke Imai and Zhichao Jiang (2018). “A Sensitivity Analysis for Missing Outcomes Due to Truncation-by-Death under the Matched-Pairs Design”, Statistics in Medicine.
data(seguro) attach(seguro) ATOPsens(Ya,Yb,Ra,Rb,Ta,Tb,gamma=0.95,l=0,u=1,alpha=0.05,rep=100)
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