ICA_t {Surrogate}R Documentation

The function ICA_t() is to evaluate surrogacy in the single-trial causal-inference framework.

Description

The function ICA_t() is to evaluate surrogacy in the single-trial causal-inference framework.

Usage

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)
)

Arguments

df

(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.

T0S0

A scalar or vector that specifies the correlation(s) between the surrogate and the true endpoint in the control treatment condition

T1S1

A scalar or vector that specifies the correlation(s) between the surrogate and the true endpoint in the control treatment condition

T0T0

A scalar that specifies the variance of the true endpoint in the control treatment condition

T1T1

A scalar that specifies the variance of the true endpoint in the control treatment condition

S0S0

A scalar that specifies the variance of the true endpoint in the control treatment condition

S1S1

A scalar that specifies the variance of the true endpoint in the control treatment condition

T0T1

A scalar or vector that contains the correlation(s) between the counterfactuals T0 and T1

T0S1

A scalar or vector that contains the correlation(s) between the counterfactuals T0 and S1

T1S0

A scalar or vector that contains the correlation(s) between the counterfactuals T1 and S0

S0S1

A scalar or vector that contains the correlation(s) between the counterfactuals S0 and S1

Value


[Package Surrogate version 3.4.1 Index]