The
AE Severity ANOVA
report screens all
adverse events
by performing a mixed-model analysis of
variance
, with average ranked severity score as the
dependent variable
and customizable fixed and
random effects
. A separate
ANOVA
is fit for each distinct adverse event.
Volcano plots
and other output enable efficient screening of adverse event severities that differ between treatment groups. If a patient has multiple instances of a particular adverse event, then those scores are averaged to form a single score for analysis.
Running this report for
Nicardipine
using default settings generates the report shown below.
The
Results
contains the following elements:
This pane enables you to access and view the output plots and associated data sets on each tab. Use the drop-down menu to view the section in the
Results
pane or remove the section and its contents from the
Results
pane.
This section shows the primary results from the analysis, including
Volcano Plot
s
and various analyses on least squares means.
The
Results
section is similar to the
LB Results
section except that
adverse events
, rather than findings, are plotted.
Refer to the
LB Results
section description for more information about the elements on this section.
The
Variability Estimates
section contains the results of a
distribution
and multivariate analysis for each sample.
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These show the distributions of each of the
variance
component estimates from the fitted
ANOVA
models, including
quantiles
and summary statistics. You can see which variance components are explaining the most variability across Findings (or
adverse event
) tests.
RSquare
is an approximation to the proportion of variability explained by the
model
. The quantiles can be useful when conducting a
power
and
sample size
exercise.
See
Distribution
for more information.
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Multivariate
Analysis.
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These plots provide a multivariate analysis of the variance component estimates, including their correlations and a
scatterplot
matrix. These reveal interrelationships between the components and how they compete to explain variability.
See
Scatterplot Matrix
for more information.
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Fit Model and Plot LS Means
: Select points or rows and click
to select
variable
(s) that uniquely define wide column names. Selected Findings tests are analyzed in the JMP Fit Model platform to view detailed fitting results and plots.
Attention
: Read the
warning
found in the link.
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Construct One-way Plots
: Click
to plot the original data in one-way format using treatment variables of your choice.
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Significant Differences Data Set
: This output data set contains a complete list of the adverse events significant by one or more criteria. This data set is indicated by the
_sig
suffix. Click
to view the data set.
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Stacked Significant Differences Data Set
: This output data set contains a complete list of all adverse events for all subjects. It is typically
very
tall.
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Experimental Design Data Set
: This is a
SAS data set
that provides information about the columns of a tall data set. It describes relevant experimental
variables
such as treatment conditions and
covariates
as well as a variable named
ColumnName.
Refer to
The Example Data
for more information. Click
to view the data set.
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Click
to view the associated data tables. Refer to
View Data
for more information.
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Click
to generate a standardized
pdf
- or
rtf
-formatted report containing the plots and charts of selected sections.
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Click
to take notes, and store them in a central location. Refer to
Add Notes
for more information.
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Click
to read user-generated notes. Refer to
View Notes
for more information.
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Click the
arrow to reopen the completed report dialog used to generate this output.
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Click the gray border to the left of the
Options
tab to open a dynamic report navigator that lists all of the reports in the review. Refer to
Report Navigator
for more information.
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Note
: For information about how treatment emergent adverse events (TEAEs) are defined in JMP Clinical, please refer to
How does JMP Clinical determine whether an Event Is a Treatment Emergent Adverse Event?
.
Include serious adverse events only
,
Event Type
,
Ignore available treatment emergent flags
,
Offset for End of Dosing
,
Additional Filter to Include Subjects
2
Merge supplemental domain
,
Filter to Include Adverse Events
,
Select the population to include in the analysis
,
By Variables
LSMeans Difference Set for Volcano Plots
,
LSMeans Treatment Control Level
,
Multiple Testing Method
,
Alpha
,
-l
og
10
(p-Value) Cutoff
Add treatment group difference threshold to select significant tests
,
Treatment Group Difference Cutoff
,
Direction of the Treatment Group Difference
Include T-statistics
,
Include p-values in addition to -log
10
(p-values)
,
Plot standardized residuals
Subject-specific filters must be created using the
Create Subject Filter
report prior to your analysis.
For more information about how to specify a filter using this option, see
The SAS WHERE Expression
.