Reports | AE Bayesian Hierarchical Model

AE Bayesian Hierarchical Model
This 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 .
Report Results Description
Running this report for Nicardipine using default settings generates the tabbed Results shown below.
The Results displays the following sections: Results Sections , Volcano Plot for Odds Ratio , Volcano Plot for Difference in Proportions , Hyperparameters , and MCMC Diagnosis .
Results Sections
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.
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.
It contains the following elements:
One Data Filter .
Enables you to subset subjects based on body system or organ class, dictionary-derived term, and/or exceedance.. Refer to Data Filter for more information.
One Volcano Plot of Posterior Exceedance Probability by Odds Ratio Sized by the Number of Subjects Experiencing the Event .
In this example, markers are colored by Body System or Organ Class , and sized by the number of subjects who experience the event.
Adjust the plot using the Circle Size slider, inequality sign, and exceedance probability. Click Update Exceedance Probability to update the plot.
Refer to Volcano Plot for more information about interpreting these plots.
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.
It contains the following elements:
One Data Filter .
Enables you to subset subjects based on body system or organ class, dictionary-derived term, and/or exceedance.. Refer to Data Filter for more information.
One Volcano Plot of Posterior Exceedance Probability by Difference in Proportions Sized by the Number of Subjects Experiencing the Event .
In this example, markers are colored by Body System or Organ Class , and sized by the number of subjects who experience the event.
Adjust the plot using the Circle Size slider, inequality sign, and exceedance probability. Click Update Exceedance Probability to update the plot.
Refer to Volcano Plot for more information about interpreting these plots.
Hyperparameters
Presents a list of hyperparameters and their values.
MCMC Diagnostics
Details diagnostic information about each parameter.
Note : The MCMC Diagnostics section is not shown by default, as it contains a large set of detailed graphs. If you decide to view this section, click on it from the ResultsSection pane, select View Results Section , and allow a few moments for it to load.
It contains the following elements for each parameter:
One Histogram , and its associated nonparametric density, quantiles , and summary statistics.
One Time Series Graph tracing the parameter values over each iteration within a Chain .
This plot summarizes the autocorrelation at each Lag within a Chain .
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:
Forest Plots of Credible Intervals : Select events and click to surface the Forest Plots of Credible Intervals , containing a credible interval for each event. You can specify how to sort events, as well as the credible interval percentage, on this .
Show Events : Select events and click to view the data table containing detailed counts and statistics for each selected event.
General
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 , Group Level
Treatment or Comparison Variable to Use , Treatment or Comparison Variable
Include serious adverse events only , Ignore available treatment emergent flags
Subject Filter 3
Additional Filters
Additional Filter to Include Subjects 4
Merge supplemental domain
Select the population to include in the analysis
Filter to Include Adverse Events
Model
Fit model type
Use the following time scale for exposure time
Options
Test Treatment Level , Reference Treatment Level
Number of Burn In Samples to Discard per Markov Chain , Number of Posterior Samples per Markov Chain
Specify the Number of Independent Markov Chains , Specify the Rate of Thinning
Random seed for simulation , Specify the Seed Value
Hyperparameters
Gamma: mu_G00 , tau2_G00 , A_G , B_G , A_G00 , and B_G00
Theta: mu_T00 , tau2_T00 , A_T , B_T , A_T00 , B_T00
Lambda: L_A , L_B

1
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.

2
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.

3
Subject-specific filters must be created using the Create Subject Filter report prior to your analysis.

4
For more information about how to specify a filter using this option, see The SAS WHERE Expression .