Repeated measures 2x3 design on SPSS

#1
My data has two factors. Factor 1 has 2 levels and Factor 2 has 3 levels.

ie a 2x3 design. Right? The study is within-subjects.

So on SPSS, I went to General Linear Model -> Repeated Measures and entered factor 1 (2) and factor 2 (3). But then when I go to define it, SPSS gives me:
1,1
1,2
1,3
2,1
2,2
2,3

Well I don't have a 1,3. :shakehead (this emoji portrays my exact state)


I'm probably not even using the right statistic. I don't understand what the 1,3 is supposed to be when I entered in that factor 1 only has 2 things.

Can anyone help me?
Thanks
 

Karabiner

TS Contributor
#2
This would have better been posted to the SPSS-subforum. But anyway.

If this is a purely within-subject (repeated measures)-design, then you have 6 measurements for each participant. In SPSS, you should have 6 columns then.

Each measurement (column) belongs to a certain combination of factor A and factor B.

E.g. 1,3 is the column which contains the measurements taken on level 1 of factor A in combination with level 3 of factor B.

With kind regards

Karabiner
 
#3
Thank you karabiner.

I see what you mean and my design is not a normal one I guess (or maybe it is but it hasn't a different name idk).

I have (using letters as the second one to distinguish them):
1,A
1,B
2,A
2,B
2,C

There is no 1,C. The teacher designed it and calls it a 2x3, but the C only happens once. There are only 5 columns of data. :( I would say it's still within-subjects because everyone did all of these.

I'm thinking maybe I want to compare A vs B vs C?
So that would be:
A,1
A,2
B,1
B,2
C
But that's not how the teacher set it up on the sheet and that doesn't really help with the C, does it? :shakehead

Do you know what test I would need to do for this or what this is?

Thanks again
 

Karabiner

TS Contributor
#4
The simplest way would be to treat this as a single factor with 5 levels, and perform pairwise post-hoc comparions between levels, if the repeated-measures ANOVA gives a statistically significant omnibus test.

With kind regards

Karabiner