Output Overview Descriptions | Clinical Reports | AE Bayesian Hierarchical Model

AE Bayesian Hierarchical Model
The AE Bayesian Hierarchical Model report fits the multi-level Bayesian hierarchical models of Berry and Berry (2004) 1 and Xia, Ma, and Carlin (2011) 2 . Adverse events are modeled, taking into account a grouping variable , such as system organ class .
Running this report for Nicardipine using default settings generates the tabbed Results window shown below. Refer to the AE Bayesian Hierarchical Model requirements description for more information.
The Results window contains the following panes:
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.
The following sections are generated by this report:
Volcano Plot for Odds Ratio : Contains a volcano plot of the posterior exceedance probability by odds ratio sized by the number of subjects experiencing each event.
Volcano Plot for Difference in Proportions : Contains a volcano plot of the posterior exceedance probability by difference in proportions sized by the number of subjects experiencing each event.
Hyperparameters : Presents a list of hyperparameters and their values.
MCMC Diagnostics : Details diagnostic information about each parameter.
Caution : The MCMC Diagnostics tab is not shown in the Tab Viewer by default, as it contains a large set of detailed graphs. If you decide to view this tab, click on it from the ResultsSection pane, select View Results Section , and allow a few moments for it to load.
Drill Down Buttons
Drill down buttons, provide you with an easy way to drill down into your data. The following drill down buttons are generated by this report:
Forest Plots of Credible Intervals : Select events and click to surface the Forest Plots of Credible Intervals window, containing a credible interval for each event. You can specify how to sort events, as well as the credible interval percentage, on this window.
Show Events : Select events and click to view the data table containing detailed counts and statistics for each selected event.
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 process dialog used to generate this output.
Note : For information about how treatment emergent adverse events (TEAEs) are defined in JMP Clinical, please refer to Determining If an Event Is a Treatment Emergent Adverse Event .

Berry, S.M., and Berry, D.A. (2004). Accounting for Multiplicities in Assessing Drug Safety:
A Three-Level Hierarchical Mixture Model. Biometrics 60 , 418-426.

Xia, H.A., Ma, H., and Carlin, B.P. (2011). Bayesian Hierarchical Modeling for Detecting Safety Signals in Clinical Trials. Journal of Biopharmaceutical Statistics 21 , 1006-1029.