estimate_ICA_OrdOrd: Estimate ICA in Ordinal-Ordinal Setting

In Surrogate: Evaluation of Surrogate Endpoints in Clinical Trials

Estimate ICA in Ordinal-Ordinal Setting

Description

estimate_ICA_OrdOrd() estimates the individual causal association (ICA) for a sample of individual causal treatment effects with an ordinal surrogate and true endpoint. The ICA in this setting is defined as follows:

R^2_H = \frac{I(\Delta S; \Delta T)}{\min \{H(\Delta S), H(\Delta T) \}}

where I(\Delta S; \Delta T) is the mutual information, and H(\Delta S) and H(\Delta T) the entropy of \Delta S and \Delta T, respectively.

Usage

estimate_ICA_OrdOrd(delta_S, delta_T)

Arguments

delta_S	(integer) Vector of individual causal treatment effects on the surrogate.
delta_T	(integer) Vector of individual causal treatment effects on the true endpoint.

Value

(numeric) Estimated ICA

Surrogate documentation built on June 8, 2025, 1:09 p.m.