plot.Predict.Treat.ContCont {EffectTreat}

Plots the distribution of the individual causal effect based on S.

Description

Plots the distribution of \Delta T_j|S_j and the 1-\alpha% CIs for the mean and median \rho_{T0T1} values (and optionally, for other user-requested \rho_{T0T1} values).

Usage

## S3 method for class 'Predict.Treat.ContCont'
plot(x, Xlab, Main, Mean.T0T1=FALSE, Median.T0T1=TRUE,  
Specific.T0T1="none", alpha=0.05, Cex.Legend=1, ...)
## S3 method for class 'Predict.Treat.Multivar.ContCont'
plot(x, Xlab, Main, Mean.T0T1=FALSE, Median.T0T1=TRUE,  
Specific.T0T1="none", alpha=0.05, Cex.Legend=1, ...)

Arguments

x

An object of class Predict.Treat.ContCont or Predict.Treat.Multivar.ContCont. See Predict.Treat.ContCont or Predict.Treat.Multivar.ContCont.

Xlab

The legend of the X-axis of the plot. Default "\Delta T_j|S_j".

Main

The title of the PCA plot. Default " ".

Mean.T0T1

Logical. When Mean.T0T1=TRUE, the 1-\alpha% CI for the mean \rho_{T0T1} value (i.e., the mean of all valid \rho_{T0T1} values in x) is shown. Default FALSE.

Median.T0T1

Logical. When Median.T0T1=TRUE, the 1-\alpha% CI for the median \rho_{T0T1} value is shown. Default TRUE.

Specific.T0T1

Optional. A scalar that specifies a particular value \rho_{T0T1} for which the 1-\alpha% CI is shown. Default "none".

alpha

The \alpha level to be used in the computation of the CIs. Default 0.05.

Cex.Legend

The size of the legend of the plot. Default 1.

...

Other arguments to be passed to the plot() function.

Author(s)

Wim Van der Elst, Ariel Alonso, & Geert Molenberghs

References

Alonso, A., Van der Elst, W., & Molenberghs, G. (submitted). Validating predictors of therapeutic success: a causal inference approach.

See Also

Predict.Treat.ContCont

Examples

# Generate the vector of PCA.ContCont values when rho_T0S=.3, rho_T1S=.9, 
# sigma_T0T0=2, sigma_T1T1=2,sigma_SS=2, and the grid of values {-1, -.99, 
# ..., 1} is considered for the correlations between T0 and T1:
PCA <- PCA.ContCont(T0S=.3, T1S=.9, T0T0=2, T1T1=2, SS=2, 
T0T1=seq(-1, 1, by=.01))

# Obtain the predicted value T for a patient who scores S = 10, using beta=5,
# SS=2, mu_S=4
Predict <- Predict.Treat.ContCont(x=PCA, S=10, Beta=5, SS=2, mu_S=4)

# examine the results
summary(Predict)

# plot Delta_T_j given S_T and 95% CI  based on 
# the mean value of the valid rho_T0T1 results  
plot(Predict, Mean.T0T1=TRUE, Median.T0T1=FALSE, 
xlim=c(4, 13))

# plot Delta_T_j given S_T and 99% CI  using 
#  rho_T0T1=.8   
plot(Predict, Mean.T0T1=FALSE, Median.T0T1=FALSE, 
Specific.T0T1=.6, alpha=0.01, xlim=c(4, 13))