## variable names in the input data.frame aeanonym
## RAND treatment as randomized
## PREF adverse event symptom name
## SN number of patients in treatment group
## SAE number of patients in each group for whom the event PREF was observed
##
## Input sort order is PREF/RAND
data(aeanonym)
head(aeanonym)
## Calculate log relative risk and confidence intervals (95% by default).
## logrelrisk sets the sort order for PREF to match the relative risk.
aeanonymr <- logrelrisk(aeanonym)
head(aeanonymr)
## construct and print plot on current graphics device
ae.dotplot(aeanonymr,
A.name="TREATMENT A (N=216)",
B.name="TREATMENT B (N=431)")
## export.eps(h2("stdt/figure/aerelrisk.eps"))
## This looks great on screen and exports badly to eps.
## We recommend drawing this plot directly to the postscript device:
##
## trellis.device(postscript, color=TRUE, horizontal=TRUE,
## colors=ps.colors.rgb[
## c("black", "blue", "red", "green",
## "yellow", "cyan","magenta","brown"),],
## onefile=FALSE, print.it=FALSE,
## file=h2("stdt/figure/aerelrisk.ps"))
## ae.dotplot(aeanonymr,
## A.name="TREATMENT A (N=216)",
## B.name="TREATMENT B (N=431)")
## dev.off()
## smaller artifical example with the wide format
aewide <- data.frame(Event=letters[1:6],
N.A=c(50,50,50,50,50,50),
N.B=c(90,90,90,90,90,90),
AE.A=2*(1:6),
AE.B=1:6)
aewtol <- aeReshapeToLong(aewide)
xr <- logrelrisk(aewtol)
ae.dotplot(xr)
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