Reports | Cluster Subjects within Study Sites

Cluster Subjects within Study Sites
Cluster Subjects within Study Sites clusters subjects within study site for the purpose of identifying similar subjects. It constructs a cross domain data set using as much data as possible (subject to user options). Next, it calculates Euclidean distances to compute a distance matrix and performs hierarchical clustering of subjects within each study center. Findings values are averaged by USUBJID , test code, visit number, and time point (if available) if there are multiple measurements for a visit or time point. The goal of this exercise is to identify pairs of subjects with a very small distance. This could be an indication that these subject are slightly modified copies of one another.
Report Results Description
Running this report for Nicardipine using default settings generates the report shown below.
The Cluster Subjects Within Study Sites report shows the results of clustering of the subjects on the basis of different combinations of covariates. The results for each grouping are presented in a separate “section”.
Results Section
This pane enables you to access and view the output plots and associated data sets on each section. Use the drop-down menu to view the section in the Results pane or remove the section and its contents from the Results pane.
Note : You might need to expand this pane to surface a scroll bar if the number of sections exceeds the spaces allotted.
Between-Subject Distance Summary
This section presents box plots of the pairwise Euclidian Distances between subjects presented by site. The Euclidian Distance is calculated within study site. A Box Plot of the minimum pairwise distance taken from each site presented is shown below.
It contains the following elements:
One set of Box Plot s of Between-Subject Distances by Site .
This figure shows box plots of all pairwise Euclidian distances within each study site. Values closer to zero (0) reflect subjects that are very similar to one another, which could indicate that they are slightly modified copies.
This enables you to subset subjects based by study site. Refer to Data Filter for more information.
One Box Plot of Minimum Between-Subject Distances for Each Site .
The box plot of minimum pairwise distances provides some idea of the most similar subjects within each site.
Site XX Distance Matrix
The Site XX Distance Matrix section is shown below. There is one section for each study site in the trial. However, only the site with the minimum pairwise distance is initially opened to minimize effects on performance. A box plot of all pairwise distances is presented as well as a Heat Map and Hierarchical Clustering display (using the Average method) to determine whether there are sets of subjects that are very similar.
It contains the following elements:
One Box Pot
Summarizes the distribution of all pairwise Euclidian distances within site XX. Small pairwise distances can be selected in the Box Plot and highlighted in the Hierarchical Clustering Heat Map with the Show Rows in Heat Map button.
One Hierarchical Clustering display.
Clusters subjects based on the pairwise Euclidian distances summarized in the box plot . Bluer color indicates subjects that are more similar, whereas red shows subjects less similar. The clustering dendrogram is presented to the right of the heat map and can show sets of more than two subjects that are similar to one another.
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:
Profile Subjects : Select subjects and click to generate the patient profiles. See Profile Subjects for additional information.
Show Subjects : Select subjects and click to open the ADSL (or DM if ADSL is unavailable) of selected subjects.
Show Rows in Heat Map : Select points that represent pairs of subjects in the Box Plot s and click to highlight the subjects within the Heat Map and Dendrogram to see how they cluster together.
Subset Clustering : On a subgroup clustering page, subsets clustering to subjects, based on pairs selected from corresponding box plot.
Revert Clustering : Click to return a subset clustering to the original state where all subjects are clustered.
Output includes one summary data set (named cswss_sum_XXX 1 , by default) containing one record per subject with selected data, one data set of all pairwise distances within the site (named cswss_alldist_XXX , by default), one data set containing minimum pairwise distances for each site (named cswss_mindist_XXX ), by default), one data set per site containing pairwise distances (named cswss_p_Y_XXX , by default, where Y is site number or indexed 1 to the number of sites) and one data set per site containing the distance matrix of subjects within the covariate subgroup (named cswss_Y_XXX , by default, where Y is site number or indexed 1 to the number of sites).
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.
No testing is performed. Subjects are clustered within each site according to the selected clustering methodology. See statistical details for hierarchical clustering in the JMP documentation.
Report Options
Report Option Descriptions
Specific documentation for each of the options can be viewed by clicking on the following links:
General Options
Age and Sex , Findings domains , Intervention domains , and/or Event domains
Analyze all tests from all findings domains , Findings Tests
Include events or interventions experienced by at least this percent of patients:
Summarize subgroups with at least this many subjects
Remove all variables with missing values , Remove variables from analysis with a missing data percentage of at least:
Sex , Race , and/or Country
Hierarchical Clustering Method
Subject Filter 2
Additional Filters
Additional Filter to Include Subjects 3
Select the population to include in the analysis

The _XXX designation is used to designate a one- to three-digit number that is added sequentially to prevent overwriting of existing data sets.

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 .