ICA_t() is to evaluate surrogacy in the single-trial causal-inference framework.The function ICA_t() is to evaluate surrogacy in the single-trial causal-inference framework.
ICA_t(
df,
T0S0,
T1S1,
T0T0 = 1,
T1T1 = 1,
S0S0 = 1,
S1S1 = 1,
T0T1 = seq(-1, 1, by = 0.1),
T0S1 = seq(-1, 1, by = 0.1),
T1S0 = seq(-1, 1, by = 0.1),
S0S1 = seq(-1, 1, by = 0.1)
)Total.Num.Matrices: An object of class numeric that contains the total number of matrices that can be formed as based on the user-specified correlations in the function call.
Pos.Def: A data.frame that contains the positive definite matrices that can be formed based on the user-specified correlations. These matrices are used to compute the vector of the \(\rho_{\Delta}\) values.
rho: A scalar or vector that contains the individual causal association \(\rho_{\Delta}\)
ICA: A scalar or vector that contains the individual causal association \(\rho_{\Delta}^2=ICA\)
ICA_t: A scalar or vector that contains the individual causal association \(ICA_{t}\)
Sigmas: A data.frame that contains the \(\sigma_{\Delta T}\) and \(\sigma_{\Delta S}\)
(numeric) is degree of freedom \(\nu\). The maximum value for \(df\) is 342. When \(df\) exceeds this threshold, the model behavior aligns with the Individual Causal Association (ICA) under the normal causal model.
A scalar or vector that specifies the correlation(s) between the surrogate and the true endpoint in the control treatment condition
A scalar or vector that specifies the correlation(s) between the surrogate and the true endpoint in the control treatment condition
A scalar that specifies the variance of the true endpoint in the control treatment condition
A scalar that specifies the variance of the true endpoint in the control treatment condition
A scalar that specifies the variance of the true endpoint in the control treatment condition
A scalar that specifies the variance of the true endpoint in the control treatment condition
A scalar or vector that contains the correlation(s) between the counterfactuals T0 and T1
A scalar or vector that contains the correlation(s) between the counterfactuals T0 and S1
A scalar or vector that contains the correlation(s) between the counterfactuals T1 and S0
A scalar or vector that contains the correlation(s) between the counterfactuals S0 and S1