# AEdotplot

##### AE (Adverse Events) dotplot of incidence and relative risk

A three-panel display of the most
frequently occurring AEs in the active arm of a clinical
study. The first panel displays their incidence by
treatment group, with different symbols for each
group. The second panel displays the relative risk
of an event on the active arm relative to the
placebo arm, with 95% confidence intervals for a $2\times2$ table.
By default, the AEs are ordered by
relative risk so that events with the largest
increases in risk for the active treatment are
prominent at the top of the display.
By setting the argument `sortbyRelativeRisk=FALSE`

, the AEs retain
the order specified by the levels of the factor.
The third panel displays the numerical values of number of patients for
each treatment,
number of adverse events for each treatment, and relative risk.
The third panel can be suppressed by the `print`

method.

##### Usage

`AEdotplot(xr, ...)` ## S3 method for class 'formula':
AEdotplot(xr, groups=NULL, data=NULL,
sortbyRelativeRisk=TRUE,
...,
sub=list(deparse(this.call[1:4],
width.cutoff=500), cex=.7))

##### Arguments

- xr
- For the formula method, a formula of the form
`AE ~ nAE/nTRT | OrgSys`

, where the condition variable is optional. For the formula method only, the variable names are not restricted. See - groups
- Variable containing the treatment levels.
- data
`data.frame`

containing at least four variables: containing the AE name, the treatment level, the number of observed AE in that treatment level, the number of patients in that treatment group. It may also contain a fifth variable- sortbyRelativeRisk
- logical. If
`TRUE`

, then make the Adverse Events an ordered factor ordering by relative risk. If`FALSE`

, then make the Adverse Events an ordered factor retaining the order of the input levels. - sub
- Subtitle for the plot. The default value is the command that generates the plot.
- ...
- Any of the arguments listed in the
calling sequence for the methods documented in
`AEdotplot.data.frame`

.

##### Details

The first panel is an ordinary dotplot of the percent of AE observed for each treatment by AE.

The second panel shows relative risk of an event on the Treatment B arm
(usually the active compound)
relative to the Treatment A arm (usually the placebo), with 95% confidence
intervals for a $2\times2$ table. Confidence intervals on the log
relative risk are calculated using the asymptotic standard error
formula given as Equation 3.18 in Agresti A., *Categorical Data
Analysis.* Wiley: New York, 1990.

By default the `AEdotplot`

function sorts the events by relative risk.
To retain the sort order implied by the `levels`

of the AE
factor, specify the argument `sortbyRelativeRisk=FALSE`

.
To control the sort order, make the AE factor in the input dataset
an `ordered`

factor
and specify the levels in the order you want.

The third panel shows the numerical values of the number and percent
of observed events on each arm and the relative risk.
The display of third panel can be suppressed by specifying the
`panel.widths`

argument. See the discussion of the
`panel.widths`

in `AEdotplot.data.frame`

.

##### Value

- The primary interest is in the display of the plot.
The function returns an

`AEdotplot`

object which is a list of three`trellis`

objects, one for the the Percent plot, one for the Relative Risk plot, and one for the Text plot containing the table of input values. The object has attributes`main`

and`sub`

hold the main and subtitles. Each must be a list containing the text in the first component.`ae.key`

is a key as described in`xyplot`

.`n.events`

is a vector containing the number of events in each subpanel.`panel.widths`

is a vector of relative widths of the three components of the graph. The numbers must sum to one. Zero values are permitted. The first width includes the left axis and the Percent plot. The second is the Relative Risk plot, and the third is the plot of the table values.`AEtable`

is a table containing the data plotted on its row.

##### References

Ohad Amit, Richard M. Heiberger, and Peter W. Lane. (2008)
``Graphical Approaches to the Analysis of Safety Data from Clinical Trials''.
*Pharmaceutical Statistics*,
**7**, 1, 20--35.

##### See Also

##### Examples

```
## formula method. See ?AEdotplot.data.frame for other methods.
data(AEdata)
head(AEdata)
AEdotplot(AE ~ nAE/nTRT, groups = TRT, data = AEdata)
AEdotplot(AE ~ nAE/nTRT | OrgSys, groups = TRT, data = AEdata)
AEdotplot(AE ~ nAE/nTRT | OrgSys, groups = TRT,
data = AEdata[c(AEdata$OrgSys %in% c("GI","Resp")),])
## test sortbyRelativeRisk=FALSE
ABCD.12345 <- AEdata[1:12,]
head(ABCD.12345)
AEdotplot(AE ~ nAE/nTRT | OrgSys, groups=TRT, data=ABCD.12345)
AEdotplot(AE ~ nAE/nTRT | OrgSys, groups=TRT, data=ABCD.12345, sort=FALSE)
## suppress third panel
tmp <- AEdotplot(AE ~ nAE/nTRT, groups = TRT, data = AEdata)
print(tmp, AEtable=FALSE)
```

*Documentation reproduced from package HH, version 3.1-19, License: GPL (>= 2)*