stepp_plot: A function to generate the stepp plots

In stepp: Subpopulation Treatment Effect Pattern Plot (STEPP)

A function to generate the stepp plots

Description

This function will be deprecated in the future. Please use S4 classes and its generic function e.g. summary, print and plot for future development.

A method to generate the 3 stepp plots for users to examine the treatment-covariate interactions in various models data arising from two treatment arms of a clinical trial. Three plots are generated:

1. effect estimates of both treatments against the median of each subpopulation
2. effect differences (in absolute scale) between the two treatments against the median of each subpopulation.
3. effect ratios (in relative scale) between the two treatments against the median of each subpopulation.

Usage

  stepp_plot(x, legendy = 30, pline = -2.5, color = c("red", "black"), 
    ylabel= "Specify Timepoint & Endpoint", xlabel="Subpopulations by Median Covariate", 
    ncex = 0.7, tlegend=c("Specify 1st Treatment", "Specify 2nd Treatment"), 
    nlas = 0, alpha = 0.05, pointwise = FALSE, ci = TRUE, pv = TRUE, 
    showss = TRUE, ylimit=c(0,100,-100,100,0,3), which="", 
    noyscale=FALSE, at=NA, subplot=FALSE) 

Arguments

x	the steppes object returned from stepp, analyze.KM.stepp or analyze.CumInc.stepp
legendy	optional - the vertical location of the legend according to the units on the y-axis; default is 30
pline	optional - specify the vertical location of the p-value, that is, on which MARgin line, starting at 0 counting outwards; default is -2.5
color	optional - a vector containing the line colors for the 1st and 2nd treatment, respectively; default is "red" and "black"
ylabel	optional - specify the label for the y-axis; default is "Specify Timepoint & Endpoint"
xlabel	optional - specify the label for the x-axis; default is "Subpopulations by Median Covariate"
ncex	optional - specify the size of the text for the sample size annotation, that is, the character expansion factor; default is 0.7
tlegend	optional - a vector containing the treatment labels, 1st and 2nd treatment, respectively; default is c("Specify 1st Treatment", "Specify 2nd Treatment"
nlas	optional - specify the las paramter (0,1,2,3) to determine the orientation of the sample size annotation; default is 0
alpha	optional - specify the significance level; default is 0.05
pointwise	optional - specify pointwise confidence intervals (pointwise=TRUE), or confidence bands; default is FALSE
ci	optional - specify if you want to display the conf. interval or band; default is TRUE
pv	optional - pvalue will be displayed in the plots; FALSE: pvalue will not be displayed in the plots; default is TRUE
showss	optional - specify the label for the x-axisoptional - show the sample size; FALSE: sample size will not be shown in the plots; default is TRUE
ylimit	optional - pvalue will be displayed in the plots; FALSE: pvalue will not be displayed in the plots; default is TRUE
which	optional - if a subset of the plots is required, specify a subset of the numbers 1:3, which is the default
noyscale	optional - do not scale to the y-axis; default is FALSE
at	optional - specify the horizontal position of the p-value; use together with pline; default is at the minimal value of x
subplot	optional - generate a subpopulation distribution subplot on top of the first STEPP plot; default is FALSE (no subplot)

Details

This is the function to generate three stepp plots for user to explore treatment-covariate interactions in various models data arising from two treatment arms of a clinical trial. You can choose to produce a single figure with all the three plots or only a subset of these through the use of the ‘which’ argument.

Through these plots, the user can examine the differences in effects (either in absolute or relative scale) with respect to each subpopulation.

This is mainly a graphics function. The STEPP analysis is done. Most of the parameters are for graphics control so that one can customize the plots for presentation purposes.

Warning

This function together with other old functions will be depreciated in the future. A new set of S4 classes are implemented to replace old interfaces. Please use them for future development.

Author(s)

Wai-ki Yip, David Zahrieh, Marco Bonetti, Bernard Cole, Ann Lazar, Richard Gelber

See Also

The S4 classes: stwin, stsubpop, stmodelKM, stmodelCI, stmodelCOX, stmodelGLM, and steppes.

Old functions to be deprecated: stepp, stepp_summary, stepp_print, analyze.KM.stepp and analyze.CumInc.stepp.

Examples

  # see example in the documentation for the function stepp.

stepp documentation built on June 18, 2022, 5:06 p.m.