Reports | AE Severity ANOVA

AE Severity ANOVA
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.
Report Results Description
Running this report for Nicardipine using default settings generates the report shown below.
The Results contains the following elements:
Results Section
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.
Variability Estimates
Shows the analyses on variance component estimates from the ANOVA model fits.
The Variability Estimates section contains the results of a distribution and multivariate analysis for each sample.
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.
Multivariate Analysis.
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.
Action Buttons
Action buttons, provide you with an easy way to drill down into your data. The following action buttons are generated by this report:
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.
Construct One-way Plots : Click to plot the original data in one-way format using treatment variables of your choice.
Output Data
This pane provides links to the following output data sets:
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 Open to view the data set.
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.
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 Open to view the data set.
Click to generate a standardized pdf - or rtf -formatted report containing the plots and charts of selected sections.
Click the Options arrow to reopen the completed report dialog used to generate this output.
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.
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? .
Report Options
Report Option Descriptions
Specific documentation for each of the options can be viewed by clicking on the following links:
General Options
Term Level , Treatment or Comparison Variable to Use , Treatment or Comparison Variable
Include serious adverse events only , Event Type , Ignore available treatment emergent flags , Offset for End of Dosing ,
Subject Filter 1
Additional Filters
Additional Filter to Include Subjects 2 Merge supplemental domain , Filter to Include Adverse Events , Select the population to include in the analysis , By Variables
Time Scale , Trial Time Windows
Additional Class Variables , Additional Fixed Effects , Random Effects
LSMeans Difference Set for Volcano Plots , LSMeans Treatment Control Level , Multiple Testing Method , Alpha , -l og 10 (p-Value) Cutoff
Additional Filter for Significant Tests
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 .