StatGraphTopic008 < CTSpedia

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Image	%LIGHTBOX{ image="plottable.jpg" thumbnail="tn_plottable.jpg" caption="Efficacy by Subgroup"}% Click on image to enlarge.
Title	Efficacy by Subgroup
Graph_Subgroup	General Principles
Code Added	Yes
Description	For each study (conditioned variable) depicts unadjusted 95% confidence intervals of each treatment group by race. In addition the tabular information is presented in the bottom portions of each panel.
Contributor/Email	Mat Soukup (email: Mat.Soukup@fda.hhs.gov)
Background	Endpoint is binary and the data set is from a randomly generated data set located on the OB network drive.
Special Considerations
Date	Original
Original Date	2007
Modified Date
Use/Suitability	Exploration
Software Program	R
Software
R-Code - Attachment	R-script: Efficacy by Subgroup - Attached
R-Code	dat <- read.csv('//cdsnas/oebdbdms/Graphics/Datasets/CleanTrial.csv')<br />base <- subset(dat, visit==2)<br />eot <- subset(dat, visit==6)<br /> eot$binep <- ifelse(base$catvar-eot$catvar >= 2, 1, 0) # Suppose this actually is from two studies eot$study <- rep(c('Study 1','Study 2', 'Study 1', 'Study 2'),<br /> c(450,300,450,300)) ss <- with(eot, summarize(100binep, llist(racef, study, trtf), <br /> smean.cl.normal)) ss$xaxis <- rep(1:4, each=4)+rep(c(-.1,.1), 8)<br /> names(ss)[4] <- 'binep'<br /> # Calculate counts and sample sizes for the table a1 <- with(eot[eot$study%in%'Study 1',], ftable(trtf, racef, binep))<br /> xs1 <- a1[,2]<br /> n1 <- a1[,1]+a1[,2]<br /> a2 <- with(eot[eot$study%in%'Study 2',], ftable(trtf, racef, binep))<br /> xs2 <- a2[,2]<br /> n2 <- a2[,1]+a2[,2]<br /> xpos <- c(.85,1.85,2.85,3.85,1.15,2.15,3.15,4.15)<br />cols <- rep(c('black','seagreen2'),each=4)<br /> #png('C:/Research/Graphics/Graphs4Display/webpages/classes/pages/images/plottable.png', # width=700, height=700) new.line <- trellis.par.get('superpose.line')<br />new.line$col <- c('black','seagreen2')<br />new.line$lty <- c(1,1,1,1)<br />new.symbol <- trellis.par.get('superpose.symbol')<br />new.symbol$col <- c('black', 'seagreen2')<br />new.symbol$pch <- c(1, 4, 16, 8)<br />trellis.par.set('superpose.line', new.line) trellis.par.set('superpose.symbol', new.symbol) xYplot(Cbind(binep,Lower,Upper)~xaxis\|study, groups=trtf, data=ss, xlab='Race', ylab='Percent Responders', ylim=c(ss$Lower-15,ss$Upper+1), aspect=1, scales=list(x=list(at=1:4, labels=(unique(ss$racef))), y=list(at=seq(20,60,10), labels=as.character(seq(20,60,10)))), key=list(type='p', points=list(pch=trellis.par.get('superpose.symbol')$pch[1:2], col=trellis.par.get('superpose.symbol')$col[1:2]), text=list(levels(base$trtf), col=trellis.par.get('superpose.symbol')$col[1:2]), columns=2, cex=1.25, title='Treatment')) # Overall means of the study oo <- with(eot, summarize(100binep, llist(study,trtf), mean))<br /> trellis.focus('panel',1,1, highlight=FALSE) panel.abline(h=oo[1:2,3], col=trellis.par.get('superpose.symbol')$col[1:2], lty=c(2,2)) for(i in 1:8){ ltext(x=xpos[i], y=8, labels=bquote(frac(.(xs1[i]),.(n1[i]))), cex=.95, col=cols[i]) } panel.abline(h=14, col='grey60') trellis.unfocus() trellis.focus('panel',2,1, highlight=FALSE) panel.abline(h=oo[3:4,3], col=trellis.par.get('superpose.symbol')$col[1:2], lty=c(2,2)) for(i in 1:8){ ltext(x=xpos[i], y=8, labels=bquote(frac(.(xs2[i]),.(n2[i]))), cex=.95, col=cols[i]) } panel.abline(h=14, col='grey60') trellis.unfocus() t1 <- with(eot[eot$study%in%'Study 1',], table(trtf))<br />t2 <- with(eot[eot$study%in%'Study 2',], table(trtf))<br /> trellis.focus('strip', 1, 1, highlight=FALSE) ltext(x=0.025, y=.5, paste('N=', t1[1], sep=''), col=c('black'), adj=c(0,NA), cex=.9) ltext(x=0.975, y=.5, paste('N=', t1[2], sep=''), col=c('seagreen2'), adj=c(1,NA), cex=.9) trellis.unfocus() trellis.focus('strip', 2, 1, highlight=FALSE) ltext(x=0.025, y=.5, paste('N=', t2[1], sep=''), col=c('black'), adj=c(0,NA), cex=.9) ltext(x=0.975, y=.5, paste('N=', t2[2], sep=''), col=c('seagreen2'), adj=c(1,NA), cex=.9) trellis.unfocus() #dev.off()
SAS-Code - Attachment
SAS-Code
Stata-Code - Attachment
Stata-Code
Other Code - Attachment
Other Code
Keywords	subgroup analysis, conditioned variable, confidence intervals, treatment groups
OPTIONAL FIELDS
References	This graphic relies extensively on the use of the trellis.focus function which allows one to zoom into parts of the trellis graphic and add annotations.
Datasets
Data
Attached Data
CATEGORIZATIONS
Classification-Evaluation	Efficacy
Classification-Graph Type	Scatterplot
Graph_Type	Scatterplot
Variable Relationship	Continuous versus Categorical
Data Types	Categorical and Continuous
Special Cases
Disclaimer	The views expressed within CTSpedia are those of the author and must not be taken to represent policy or guidance on the behalf of any organization or institution with which the author is affiliated.
Permission	Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF ERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT OLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Reference Image

This topic: CTSpedia > WebHome > StatGraphHome > ContributeGraphics > StatGraphTopic008
Topic revision: 30 Mar 2012, MaryBanach

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