I have a data set that looks like this:
GROUP WEEK1 WEIGHT(kg) WEEK2 WEIGHT(kg) WEEK3 WEIGHT(kg)
Control
Subject C1 40 42 44
Subject C2 52 57 57
Subject C3 55 55 60
Subject C4 45 47 49
Experimental
Subject E1 38 40 49
Subject E2 42 47 50
Subject E3 55 60 68
Subject E4 65 77 88
My question is: What tool shall I use to test my hypothesis that the two groups (control and experimental) do not significantly differ with regard to weight?
Please note that the weights are repeated measures. I understand that if I were to examine the data per group (Control
first, then Experimental
), I'd perform a repeated measures ANOVA for control and another for experimental.
Best Answer
Even for one group only, I don't like the so-called repeated measures ANOVA because it assigns a compound symmetry variance matrix, thereby implying the same correlation between week1 and week2 and between week1 and week3, which is a contestable assumption.
But in fact I'm not sure that all statisticians are in agreement in regards to the meaning of "repeated measures ANOVA". It is more important to understand what we do than only knowing the name of what we do.
The easiest way is to assign an unstructured variance matrix, and this is the so-called MANOVA (by the way, here I was asking about an intermediate between compound symmetry and unstructured).
In the SAS language, your model would be
Setting
TYPE=UN
is the MANOVA with the group factor. SettingTYPE=CS
is the "classical" repeated-measures ANOVA with the group factor.