plot.SPF.BinCont {Surrogate}

Plot the surrogate predictive function (SPF) in the causal-inference single-trial setting in the binary-continuous case.

Description

This function is used to create several plots related to the surrogate predictive function (SPF) in the single-trial setting within the causal-inference framework when the surrogate endpoint is continuous (normally distributed) and the true endpoint is a binary outcome. For details, see Alonso et al. (2024).

Usage

## S3 method for class 'SPF.BinCont'
plot(x, Histogram.SPF=TRUE, Causal.necessity=TRUE, Best.pred=TRUE, Max.psi=TRUE, ...)

Arguments

x

A fitted object of class SPF.BinCont. See SPF.BinCont.

Histogram.SPF

Logical. Should histograms of SPF be provided? When it is requested, a matrix of histograms illustrating various combination of the SPF, i.e., the P[\Delta T | \Delta S \in I_{ab}], will be produced. Default Histogram.SPF=TRUE.

Causal.necessity

Logical. Should a histogram showing the P[\Delta T = 0 | \Delta S = 0] be provided? Default Causal.necessity=TRUE.

Best.pred

Logical. Should a bar plot showing the frequency of \tilde{\psi}_{ab}=i for each interval (x,y) be provided? Default Best.pred=TRUE.

Max.psi

Logical. Should a histogram showing the P[\Delta T = \tilde{\psi}_{ab}(\Delta S)] be provided? Default Max.psi=TRUE.

...

Extra graphical parameters to be passed to hist() or barplot().

Author(s)

Fenny Ong, Wim Van der Elst, Ariel Alonso, and Geert Molenberghs

References

Alonso, A., Ong, F., Van der Elst, W., Molenberghs, G., & Callegaro, A. (2024). Assessing a continuous surrogate predictive value for a binary true endpoint based on causal inference and information theory in vaccine trial.

See Also

SPF.BinCont

Examples

## Not run: # Time consuming code part
data(Schizo)
fit.ica <- ICA.BinCont.BS(Dataset = Schizo, Surr = BPRS, True = PANSS_Bin, nb = 10,
Theta.S_0=c(-10,-5,5,10,10,10,10,10), Theta.S_1=c(-10,-5,5,10,10,10,10,10),
Treat=Treat, M=50, Seed=1)

fit.spf <- SPF.BinCont(fit.ica, a=-5, b=5)

summary(fit.spf)
plot(fit.spf)

## End(Not run)