Filling in missing data and transposing
The raw data are structured in the way that the same subject occupies multiple rows, as shown in the following table. This is called the tall structure, as opposed to the wide structure, in which each user takes a row and each item takes a column. In this example, there are five items and Question 5 is skipped by all examinees while the other items are skipped by only some of the examinees.
It is easy to manually convert the data when there are only five items and three subjects. However, this process will be extremely tedious when there are 50 items and 3,000 examinees. Before transposing, the missing data must be filled in. The following SAS program shows you how to fill in the missing and then transpose the data.
Thanks Dr. Marlyin Thompson for her input in solving this problem.