CausalDiagramContCont: Draws a causal diagram depicting the median correlations...

In Surrogate: Evaluation of Surrogate Endpoints in Clinical Trials

Draws a causal diagram depicting the median correlations between the counterfactuals for a specified range of values of ICA or MICA in the continuous-continuous setting

Description

This function provides a diagram that depicts the medians of the correlations between the counterfactuals for a specified range of values of the individual causal association (ICA; \rho_{\Delta}) or the meta-analytic individual causal association (MICA; \rho_{M}).

Usage

CausalDiagramContCont(x, Min=-1, Max=1, Cex.Letters=3, Cex.Corrs=2, 
Lines.Rel.Width=TRUE, Col.Pos.Neg=TRUE, Histograms.Counterfactuals=FALSE)

Arguments

x	An object of class ICA.ContCont or MICA.ContCont. See ICA.ContCont or MICA.ContCont.
Min	The minimum values of (M)ICA that should be considered. Default=-1.
Max	The maximum values of (M)ICA that should be considered. Default=1.
Cex.Letters	The size of the symbols for the counterfactuals (S_0, S_1), T_0, T_1). Default=3.
Cex.Corrs	The size of the text depicting the median correlations between the counterfactuals. Default=2.
Lines.Rel.Width	Logical. When Lines.Rel.Width=TRUE, the widths of the lines that represent the correlations between the counterfactuals are relative to the size of the correlations (i.e., a smaller line is used for correlations closer to zero whereas a thicker line is used for (absolute) correlations closer to 1). When Lines.Rel.Width=FALSE, the width of all lines representing the correlations between the counterfactuals is identical. Default=TRUE.
Col.Pos.Neg	Logical. When Col.Pos.Neg=TRUE, the color of the lines that represent the correlations between the counterfactuals is red for negative correlations and black for positive ones. When Col.Pos.Neg=FALSE, all lines are in black. Default=TRUE.
Histograms.Counterfactuals	Should plots that shows the densities for the inidentifiable correlations be shown? Default =FALSE.

Author(s)

Wim Van der Elst, Ariel Alonso, & Geert Molenberghs

References

Alonso, A., Van der Elst, W., Molenberghs, G., Buyse, M., & Burzykowski, T. (submitted). On the relationship between the causal inference and meta-analytic paradigms for the validation of surrogate markers.

Van der Elst, W., Alonso, A., & Molenberghs, G. (submitted). An exploration of the relationship between causal inference and meta-analytic measures of surrogacy.

See Also

ICA.ContCont, MICA.ContCont

Examples

## Not run:  #Time consuming (>5 sec) code parts
# Generate the vector of ICA values when rho_T0S0=.91, rho_T1S1=.91, and when the
# grid of values {0, .1, ..., 1} is considered for the correlations
# between the counterfactuals:
SurICA <- ICA.ContCont(T0S0=.95, T1S1=.91, T0T1=seq(0, 1, by=.1), T0S1=seq(0, 1, by=.1), 
T1S0=seq(0, 1, by=.1), S0S1=seq(0, 1, by=.1))

#obtain a plot of ICA

# Obtain a causal diagram that provides the medians of the 
# correlations between the counterfactuals for the range
# of ICA values between .9 and 1 (i.e., which assumed 
# correlations between the counterfactuals lead to a 
# high ICA?)
CausalDiagramContCont(SurICA, Min=.9, Max=1)

# Same, for low values of ICA
CausalDiagramContCont(SurICA, Min=0, Max=.5)
## End(Not run)

Surrogate documentation built on Sept. 25, 2023, 5:07 p.m.