Surrogate (version 0.6)

plot.Fano.BinBin: Plots the distribution of \(R^2_{HL}\) either as a density or as function of \(\pi_{10}\) in the setting where both \(S\) and \(T\) are binary endpoints

Description

The function plot.Fano.BinBin plots the distribution of \(R^2_{HL}\) which is fully identifiable for given values of \(\pi_{10}\). See Details below.

Usage

# S3 method for Fano.BinBin
plot(x,Type="Density",Xlab.R2_HL,main.R2_HL,
ylab="density",Par=par(mfrow=c(1,1),oma=c(0,0,0,0),mar=c(5.1,4.1,4.1,2.1)),
Cex.Legend=1,Cex.Position="top", lwd=3,linety=c(5,6,7),color=c(8,9,3),...)

Arguments

x

An object of class Fano.BinBin. See Fano.BinBin.

Type

The type of plot that is produced. When Type="Freq", a histogram of \(R^2_{HL}\) is produced. When Type="Density", the density of \(R^2_{HL}\) is produced. When Type="Scatter", a scatter plot of \(R^2_{HL}\) is produced as a function of \(\pi_{10}\). Default Type="Scatter".

Xlab.R2_HL

The label of the X-axis when density plots or histograms are produced.

main.R2_HL

Title of the density plot or histogram.

ylab

The label of the Y-axis when density plots or histograms are produced. Default ylab="density".

Par

Graphical parameters for the plot. Default par(mfrow=c(1,1),oma=c(0,0,0,0),mar=c(5.1,4.1,4.1,2.1)).

Cex.Legend

The size of the legend. Default Cex.Legend=1.

Cex.Position

The position of the legend. Default Cex.Position="top".

lwd

The line width for the density plot . Default lwd=3.

linety

The line types corresponding to each level of fano_delta . Default linety=c(5,6,7).

color

The color corresponding to each level of fano_delta . Default color=c(8,9,3).

...

Other arguments to be passed.

Value

An object of class Fano.BinBin with components,

R2_HL

The sampled values for \(R^2_{HL}\).

H_Delta_T

The sampled values for \(H{\Delta T}\).

minpi10

The minimum value for \(\pi_{10}\).

maxpi10

The maximum value for \(\pi_{10}\).

samplepi10

The sampled value for \(\pi_{10}\).

delta

The specified vector of upper bounds for the prediction errors.

uncertainty

Indexes the sampling of \(pi1\_\).

pi_00

The sampled values for \(\pi_{00}\).

pi_11

The sampled values for \(\pi_{11}\).

pi_01

The sampled values for \(\pi_{01}\).

pi_10

The sampled values for \(\pi_{10}\).

Details

Values for \(\pi_{10}\) have to be uniformly sampled from the interval \([0,\min(\pi_{1\cdot},\pi_{\cdot0})]\). Any sampled value for \(\pi_{10}\) will fully determine the bivariate distribution of potential outcomes for the true endpoint.

The vector \(\bold{\pi_{km}}\) fully determines \(R^2_{HL}\).

References

Alonso, A., Van der Elst, W., & Molenberghs, G. (2014). Validation of surrogate endpoints: the binary-binary setting from a causal inference perspective.

See Also

Fano.BinBin

Examples

# NOT RUN {
# Conduct the analysis assuming no montonicity
# for the true endpoint, using a range of
# upper bounds for prediction errors 
FANO<-Fano.BinBin(pi1_ = 0.5951 ,  pi_1 = 0.7745, 
fano_delta=c(0.05, 0.1, 0.2), M=1000)

plot(FANO, Type="Scatter",color=c(3,4,5),Cex.Position="bottom")
# }