TrioScattorPlot: Generate Scatter Plots for Time-to-Event and Biomarkers for...

Description Usage Arguments Author(s) References See Also Examples

View source: R/TrioScattorPlot.R

Description

This function will generate the scatter plot of time-to-event and biomarker for three dataset. It helps to visualize the relationship between survival endpoints and biomarkers. It can also help to compare the three datasets

Usage

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TrioScattorPlot(data1, data2, data3, cutoff, xlab, ylab, main, ylim, xlim, col1, 
col2, col3, col4, lwd, pch1, pch2, legendloc, legendtxt, ncol)

Arguments

data1

Data object 1 with three variables included: event: the survival time, a positive numerical vector with no missing values; censor: the censor information, a vector with 1 indicating an event and 0 indicating right censored; marker: the biomarker information, or other interesting variables.

data2

Data object 2 with the same structure as data object 1.

data3

Data object 3 with the same structure as data object 1.

cutoff

This is to define the interesting data cutoff time point to see the relationship between time-to-events and markers.

xlab

It is the title for x axis; default is "Marker".

ylab

It is the title for y axis; default is "Time to Event".

main

It is the title for the plot; default is "Scattor Plot".

ylim

It creates the continuous scale of y axis of the plot; default is "c(0,3600)".

xlim

It creates the continuous scale of y axis of the plot; default is "c(0,100)".

col1

It defines the color of the dot in the dataset 1; default is "red".

col2

It defines the color of the dot in the dataset 2; default is "blue".

col3

It defines the color of the dot in the dataset 3; default is "black".

col4

It defines the color of the cutoff line; default is "tomato".

lwd

It defines the width of the cutoff line; default is "2".

pch1

It defines the type of the dot for event; default is "20".

pch2

It defines the type of the dot for censor; default is "21".

legendloc

It specifies the location of the legend; default is "bottomright".

legendtxt

It provides the text of the legend; default is "c("death-group1","censor-group1","death-group2","censor-group2",,"death-group3","censor-group3")".

ncol

It specifies the number of columns displayed in legend; default=1

Author(s)

Hui Yang huiy@amgen.com, Rui Tang rui_tang@vrtx.com and Jing Huang jinghuang0@gmail.com

References

Yang H., Tang R., Hale M. and Huang J. (2016) A visualization method measuring the performance of biomarkers for guiding treatment decisions Pharmaceutical Statistics, 15(2), 1539-1612

See Also

SoloScattorPlot, DuoScattorPlot

Examples

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	## Create three data objects for the function:

	tmppb = wpcdata[wpcdata$TRTA=="Placebo",]
	tmptrt1 = wpcdata[wpcdata$TRTA=="LowDose",]
	tmptrt2 = wpcdata[wpcdata$TRTA=="HighDose",]
	o.data1 =data.frame(event=tmppb$OSday, censor=tmppb$OScensor, marker=tmppb$Biomarker1)
	o.data2 =data.frame(event=tmptrt1$OSday, censor=tmptrt1$OScensor, marker=tmptrt1$Biomarker1)
	o.data3 =data.frame(event=tmptrt2$OSday, censor=tmptrt2$OScensor, marker=tmptrt2$Biomarker1)
	
	## Draw the scattor plot for the three data objects:
	
	TrioScattorPlot(o.data1,o.data2,o.data3,180,xlab=c("Marker"),ylab=c("Surovival Rate"),
	main=c("Weighted Predictiveness Curve"),ylim=c(0,600),xlim=c(0,100),col1="red",
	col2="black",col3="blue",lwd=2,pch1=20,pch2=21,legendloc="bottomright",ncol=1)

WPC documentation built on May 2, 2019, 6:52 a.m.