Min.R2.delta: Compute minimum R^2_{delta} for desired prediction accuracy

In EffectTreat: Prediction of Therapeutic Success

Description

Computes the minimum R^2_{δ} needed to achieve the desired prediction accuracy for the set of pretreatment predictors.

Usage

Min.R2.delta(delta, Sigma_T0T0, Sigma_T1T1)

Arguments

delta	The vector of δ values to be considered.
Sigma_T0T0	The variance of T in the control treatment group.
Sigma_T1T1	The variance of T in the experimental treatment group.

Author(s)

Wim Van der Elst, Ariel Alonso & Geert Molenberghs

References

Alonso, A., Van der Elst, W., Luaces, P., Sanchez, L., & Molenberghs, G. (submitted). Evaluating multivariate predictors of therapeutic success: a causal inference approach.

Examples

Fit <- Min.R2.delta(delta = seq(from = 0, to = 250, by=50), 
  Sigma_T0T0 = 38.606, Sigma_T1T1 = 663.917)

# Explore the results
summary(Fit)
plot(Fit)

Example output

Function call:

Min.R2.delta(delta = seq(from = 0, to = 250, by = 50), Sigma_T0T0 = 38.606, 
    Sigma_T1T1 = 663.917)

# R2_delta for different delta's:
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

  delta R^2_delta
1     0 1.0000000
2    50 0.9511107
3   100 0.9022213
4   150 0.8533320
5   200 0.8044426
6   250 0.7555533

EffectTreat documentation built on July 8, 2020, 7:17 p.m.