How do standard versus custom dimensions change the view of the data?
To understand how you might use custom data dimensions, consider the following example, which illustrates how you can use standard and custom data dimensions to look at your data in different ways.
The following sample form collects information about eye cloudiness and color in a glaucoma study.
Example of standard and custom data dimensions—Information collected
Item |
Options |
---|---|
Left eye cloudiness |
¡ Clear ¡ Moderately cloudy ¡ Very cloudy |
Left eye color |
¡ Brown ¡ Blue ¡ Green |
Right eye cloudiness |
¡ Clear ¡ Moderately cloudy ¡ Very cloudy |
Right eye color |
¡ Brown ¡ Blue ¡ Green |
If you select Subject as a standard data dimension, the data collected in the form might be stored in the following manner.
How data is stored in a standard data dimension
Subject |
Left cloud |
Left color |
Right cloud |
Right color |
---|---|---|---|---|
A |
Moderately cloudy |
Blue |
Clear |
Blue |
B |
Very cloudy |
Brown |
Very cloudy |
Brown |
C |
Clear |
Green |
Clear |
Blue |
Alternately, you might want to pivot your data on a piece of information, such as Eye.
In the following example, Subject is selected as a standard data dimension. In addition, a custom data dimension of Eye has been created with the values of Left and Right. When you add items that collect data for the left eye to the data series, you select the Left value for the custom dimension. When you add items that collect data for the right eye to the data series, you select the Right value for the custom dimension.
Data in a standard data dimension, pivoted on a custom data dimension called Eye
Subject |
Eye |
Cloudiness |
Color |
---|---|---|---|
A |
Left |
Very cloudy |
Blue |
A |
Right |
Clear |
Blue |
B |
Left |
Very cloudy |
Brown |
B |
Right |
Very cloudy |
Brown |
C |
Left |
Clear |
Green |
C |
Right |
Clear |
Blue |