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.
Running this report with the
Nicardipine
sample setting and default options generates the output shown below.
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.
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Show Sites
: Shows the rows of the data table for the selected points from the
volcano plot
.
|
opens the following table:
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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:
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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
.
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Click
to view the associated data tables. Refer to
View Data
for more information.
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Click
to generate a standardized
pdf
- or
rtf
-formatted report containing the plots and charts of selected sections.
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Click
to take notes, and store them in a central location. Refer to
View Notes
for more information.
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Click
to read user-generated notes. Refer to
View Notes
for more information.
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Click the
arrow to reopen the completed report dialog used to generate this output.
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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.
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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)?
.
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
.