Dependent t-test for matched pairs vs repeated measures I am planning an evaluation which will deploy pre- and post-tests for one group of students. I would like to perform a dependent t-test but may not be able to perform a repeated measures analysis since we may not be able to collect full names, maybe only ages from the students.
Is there any meaningful difference between a matched pairs (e.g., pairing by ages) versus repeated measures analysis? My preference would be to perform a repeated measures analysis if we could ask the students to enter their full names. If we can't collect names and have to do a matched pairs analysis using ages, would there be any disadvantage in doing so?
Thanks in advance for any feedback.
 A: Your question is really unclear.


*

*How many measures (i.e., tests of students) do you intend to deploy?  Two?  More than two?

*Are the repeated measures able to be matched up for each student?  That is to say, can you somehow collect tests in a way that you can tell that a pair (or group if the answer to item 1 above is more than two) of tests were completed by the same student?  Can you anonymize them with an ID?

*What exactly do you mean by "pair by age?"  In a typical student population, you should expect many students to be of the same age.  What happens if you have 5 students who are all the same age?  How do you "pair up" their repeated measures?  Are you suggesting you take the means of each measure in time for each observed age, and do a repeated measures test on each age?  This is obviously problematic.

*What is the hypothesis you wish to test or the inference you wish to make?


What I can say is that you cannot do a matched pairs or repeated measures test if you can only identify pairs/groups of tests by age.  The assumption for such tests requires that you can identify which observations are repeated measures on the same experimental unit.
