Transposing Data in a Data Sheet
Using the Transpose Data Function
First, let me say this function is brand new; if you run into a problem, please contact me!
The purpose of the Transpose Data function in EZAnalyze is to take data that violate the 'One Case Per Row' principle of popular data analysis programs and reconfigure the data so that it does not violate the principle, and can be used in EZAnalyze. Many student information systems used in schools construct data in such a way that this principle is violated because it is arguably a better way to put information into storage for easy retrieval (but not statistical analyses).
Since this is a little convoluted, an example may help.
| Student ID | Last Name | Date | Grade | Element Description | Score |
| 1234567 | Beenthere | 8/21/2007 | 8 | Reading Score | 2 |
| 1234567 | Beenthere | 8/21/2007 | 8 | Writing Score | 3 |
| 1234567 | Beenthere | 8/21/2007 | 8 | Math Score | 2 |
| 1234568 | Seenit | 8/21/2007 | 8 | Reading Score | 4 |
| 1234568 | Seenit | 8/21/2007 | 8 | Writing Score | 3 |
| 1234568 | Seenit | 8/21/2007 | 8 | Math Score | 3 |
| 1234569 | Donethat | 8/21/2007 | 8 | Reading Score | 1 |
| 1234569 | Donethat | 8/21/2007 | 8 | Writing Score | 2 |
| 1234569 | Donethat | 8/21/2007 | 8 | Math Score | 3 |
The data above violates the 'one case per row' principle because each student is actually on three rows; each row with a unique reading, writing or match score
To use the Transpose Function to reconfigure this data for use with EZAnalyze, select 'Other Tools' from the EZAnalyze main menu, then select 'Transpose Data.
In the 'Transposer' Dialog box, select the variable that contains your Unique Identifier (Student ID in the example above). Next, select the variable that contains a description of the data you are interested in obtaining under the 'Element Description' menu (Element Description is the variable, too, in the example). Finally, select the 'Element Value' from the list provided; this is the actual data you are interested in analyzing (Score in the example above).
OPTION:
- Delete all other data except these three items - select this if you want nothing else but the three selected columns (Unique ID, Element Description, Element value) on your data sheet. In the example above, last name, date, and grade would be deleted. You can see in the reconfigured example below what it would look like if this option was not selected.
When you click OK, a new sheet will appear that contains the reconfigured data you selected. If you ran this procedure on the data above, here is what the reconfigured data would look like:
| Student ID | Last Name | Date | Grade | Reading Score | Writing Score | Math Score |
| 1234567 | Beenthere | 8/21/2007
|
8
|
2
|
3
|
2
|
| 1234568 | Seenit | 8/21/2007
|
8
|
4
|
3
|
3
|
| 1234569 | Donethat | 8/21/2007
|
8
|
1
|
2
|
3
|
Now, these data are ready for EZAnalyze!
It is important to note that all conversions happen on a copy of your original data sheet, which will remain unharmed during this process.