Missing data for a paired t-test

Hi everyone. My question is how to handle missing data from a paired T-Test.

I am looking at pre-post survey data for a college course. The survey question are looking at students attitudes on multiple subjects, from the beginning of the course to the end of the course. I used a likert scale and course instructors were hoping that the attitudes towards the topics improved.

In the pre-test I have about 598 responses, in the post-test I have about 363 responses. Some of the students who did the pre-survey dropped the course, and some of the students who did the post survey added the course later in the quarter. My pre-post sample with completed responses for both pre-post are about 250 responses. When I do paired T-Test it seems that attitudes towards the topics improved. I am worried about non-response bias.

After conducting expectation maximization I have complete data for 700 pre-post responses. When I do the paired T-Test it appears most of the attitudes towards the topics became negative. I am worried that this method skewed the data with too many missing responses.

What would be your recommended course of action?


TS Contributor
First you could decide whether you want to perform a completer analysis, or an intention-to-treat analysis, or both.

The inclusion of the posttetst-only subjects is a bit unusual, though. What do you expect to gain by this?

With kind regards