ICA_alpha_ContCont {Surrogate}R Documentation

Assess surrogacy using a Rényi divergence based family of metrics in the causal-inference single-trial setting in normal case

Description

The function ICA_alpha_ContCont() is a set of metrics to evaluate surrogacy. ICA_alpha have the similar mathematical properties with ICA.ContCont().

Usage

ICA_alpha_ContCont(
  alpha = numeric(),
  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

alpha

(numeric) is order ⁠alpha in [0, infinity]⁠

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]