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The format is very good but continuous variables have been arbitrarily binned. The best display would preserve the continuous nature of all continuous variables.

-- FrankHarrell - 18 May 2016

 

OriginalStatGraphicsForm edit

Image
Dotplot SOC
Click on image to enlarge.
Title Dotplot of Primary SOC
Graph_Subgroup General Principles
Code Added Yes
Description The following example is a dotplot of the percent of events occurring within a system organ classification for a single treatment group. The SOC are sorted according to the relative frequency.
Contributor/Email Mat Soukup (email: Mat.Soukup@fda.hhs.gov)
Sanjay Matange (email: Sanjay.Matange@sas.com)
Background

Special Considerations

Date Original
Original Date 2007
Modified Date

Use/Suitability Presentation
Software Program R, SAS
Software R version 2.10
SAS Version 9.40M3
R-Code - Attachment R-script: Dotplot of Primary SOC
R-Code library(lattice)

set.seed(26)
soc <- c('Infections and infestations',
'Neoplasms benign and malignant (incl. cysts and polyps)',
'Blood and the lymphatic system disorders',
'Immune system disorders',
'Endocrine disorders',
'Metabolism and nutrition disorders',
'Psychiatric disorders',
'Nervous system disorders',
'Eye disorders',
'Ear and labyrinth disorders',
'Cardiac disorders',
'Vascular disorders',
'Respiratory, thoracic and mediastinal disorders',
'Gastrointestinal disorders',
'Hepato-biliary disorders',
'Skin and subcutaneous tissue disorders',
'Musculoskeletal, connective tissue and bone disorders',
'Renal and urinary disorders',
'Pregnancy, puerperium and perinatal conditions',
'Reproductive system and breast disorders',
'Congenital and familial/genetic disorders',
'General disorders and administration site conditions',
'Investigations',
'Injury and poisoning',
'Surgical and medical procedures',
'Social circumstances')
rate <- round(rnorm(length(soc), 8, 3), 1)
ratec <- as.character(rate)
# order by most frequent
dat <- data.frame(soc, rate, ratec)

sortmat <- function (Mat, Sort) {
m <- do.call("order", as.data.frame(Mat[, Sort]))
Mat[m, ]
}

sdat <- sortmat(dat, 2)

# Set up the plot
levpt <- unique(sdat$soc)
npt <- length(levpt)

png('C:/Research/Graphics/Graphs4Display/webpages/classes/pages/images/DotplotSOC.png',
width=600, height=400)

# Set-up Layout
mylayout <- layout(matrix(c(1,2,3), byrow=TRUE, ncol=3),
widths=c(4/10,1/10,5/10))

par(mar=c(5,1,2,0))
plot(x=c(0,max(nchar(as.character(sdat$soc)))+1), y=c(.9,npt+.1), ann=FALSE, axes=FALSE, type='n')
title('System Organ Classification')
text(x=rep(max(nchar(as.character(sdat$soc))), npt), y=1:npt, label=sdat$soc, adj=c(1,0.5))

par(mar=c(5,0,2,0))
plot(x=c(0,1), y=c(.9,npt+.1), ann=FALSE, axes=FALSE, type='n')
title('%')
text(x=rep(.5, npt), y=1:npt, label=sdat$ratec, adj=c(0.5,0.5))

par(mar=c(5,0,2,2))
plot(x=c(0,max(sdat$rate)+.25), y=c(.9,npt+.1), type='n', axes=FALSE,
xlab='Relative Frequency of an Event (%)', ylab='',
ylim=c(.9,npt+.1))
axis(1)
#box()
abline(v=c(0,5,10,15), col='grey80', lty=3, lwd=2)
for(i in 1:npt){
lines(c(0,sdat$rate[i]),c(i,i), lty=1, col='grey60', lwd=2)
}
points(sdat$rate, 1:npt, pch=16, col='black', cex=2)
dev.off()
SAS-Code - Attachment

SAS-Code %let gpath='.';
%let dpi=200;
ods html close;
ods listing gpath=&gpath image_dpi=&dpi;

/*--Create data set--*/
data dot;
format Pct percent8.1;
label pct='%';
label classification='System Organ Classification';
input Value Classification $6-65;
Pct=Value/100;
datalines;
1.6 Infections and infestations
11.4 Neoplasms benign and malignant (incl. cysts and polyps)
6.5 Blood and the lymphatic system disorders
10.5 Immune system disorders
6.8 Endocrine disorders
8.4 Metabolism and nutrition disorders
8.4 Psychiatric disorders
10.7 Nervous system disorders
7.9 Eye disorders
9.3 Ear and labyrinth disorders
12.8 Cardiac disorders
7.9 Vascular disorders
6.3 Respiratory, thoracic and mediastinal disorders
15.1 Gastrointestinal disorders
8.5 Hepato-biliary disorders
11.0 Skin and subcutaneous tissue disorders
8.1 Musculoskeletal, connective tissue and bone disorders
4.7 Renal and urinary disorders
2.8 Pregnancy, puerperium and perinatal conditions
10.4 Reproductive system and breast disorders
6.2 Congenital and familial/genetic disorders
9.3 General disorders and administration site conditions
15.7 Investigations
9.1 Injury and poisoning
8.8 Surgical and medical procedures
5.3 Social circumstances
;
run;

/*--Sort by descending pct--*/
proc sort data=dot out=dot_Sort;
by descending pct;
run;

/*--Create Dot Plot using SAS 9.40M3--*/
ods graphics / reset width=5in height=3in imagename='Dotplot_of_Primary_SOC';
proc sgplot data=dot_sort noborder;
dropline y=classification x=pct / dropto=y;
scatter y=classification x=pct / markerattrs=(symbol=circlefilled);
yaxistable classification pct / location=outside position=left pad=10
valuejustify=right valueattrs=(size=7) labelattrs=(size=8);
xaxis min=0 grid offsetmin=0 label='Relative Frequency of an Event';
yaxis fitpolicy=none valueattrs=(size=7) reverse display=none;
run;
Stata-Code - Attachment

Stata-Code

Other Code - Attachment

Other Code

Keywords safety, events, system organ classification, treatment group
OPTIONAL FIELDS

References

Datasets

Data

Attached Data

CATEGORIZATIONS

Classification-Evaluation Safety
Classification-Graph Type Dotplot
Graph_Type Dotplot
Variable Relationship Continuous versus Categorical
Data Types Categorical and Continuous
Special Cases

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Reference Image DotplotSOC_reference_200.png
Topic revision: r17 - 18 May 2016 - 07:12:20 - FrankHarrell
 

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