Reports | Perfect Scheduled Attendance

Perfect Scheduled Attendance
This report compares the distribution of study visit days for each center compared to all other centers combined, and identifies unusual differences. For example, a site where all visits occur on the same study day can be flagged for further investigation.
Report Results Description
Running this report with the Nicardipine sample setting and default options generates the output shown below.
The Perfect Scheduled Attendance report initially shows one Volcano Plot .
Each point represents the comparison of a site to all other sites. This comparison is used to determine whether there is a difference in distribution for perfect attendance and is done for all sites across all tests in all findings domains.
The Y axis is the -log 10 (Row Mean Score p-value ). Large numbers indicate statistically significant results.
The X axis is the maximum percent difference across all visits between a site versus all sites.
Values far from 0 indicate important differences between a site and the reference distribution of all other sites. An FDR line is indicated by the dotted red line. Values above this line (Such as site 39, above) can be considered significant adjusting for multiple comparisons. This could identify rounding issues or other problems with how a site reports a particular test compared to other sites.
Note : In the example shown above, the vast majority of the study sites (circled above) show little or no differences in Perfect attendance. In fact, the points representing these sites overlap such that individual sites cannot be differentiated at this scale.
You can use the available options to drill-down into the data
Action Buttons
Action buttons, provide you with an easy way to drill down into your data. Use your mouse to select one or more sites of interest (as shown for site 39, above) , as shown below, before clicking one of the action buttons:
The following action buttons are available:
Show Sites : Shows the rows of the data table for the selected points from the volcano plot .
Clicking opens the following table:
In this example, only site 39 showed a near perfect attendance and only for Visit 1.
Visit Bar Charts : For the points selected in the volcano plot, clicking displays a bar chart comparing the percent of subjects with perfect attendance between selected sites versus all others. This gives the user the ability to compare just how different each site is scheduled attendance. The underlying data table is available by going to Script > Data Table . The following chart shows the sites/tests selected above:
Data Filter
This enables you to subset your data based on study site and/or visit number. Refer to Data Filter for more information about how to use the Data Filter .
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.
This report compares the observed distribution of study day for each visit with each site compared to all other sites taken together as a reference. The comparison is made using a row mean score chi -square tests as described for Digit Preference , with study day replacing digit as the column variable.
Alternatively, exact Mantel-Haenszel p -values can be computed. The Mantel-Haenszel chi -square statistic tests the alternative hypothesis that there is a linear association between the row variable and the column variable. Both variables must lie on an ordinal scale. The Mantel-Haenszel chi -square statistic is computed as (n-1)r^2 where r is the Pearson correlation between the row variable and the column variable. 5000 samples (default) are used to compute resampling p -value, which is the proportion of resampled values that are more extreme the observed p -value.
FDR p -values are calculated and the reference line is determined as described in How does JMP Clinical calculate the False Discovery Rate (FDR)? .
Report Options
Report Option Descriptions
Specific documentation for each of the options can be viewed by clicking on the following links:
General Options
Summarize sites with at least this many subjects:
Calculate exact Mantel-Haenszel p-values
Number of Monte-Carlo Samples
Subject Filter 1
Additional Filters
Additional Filter to Include Subjects 2
Select the population to include in the analysis

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 .