Repeated Anova - Within and Between factors

[stanmarciano]

Reposting this from here: https://communities.sas.com/t5/SAS-Statistical-Procedures/Anova-Analyzing-experiment-with-within-and...

Hi I have an experiment with one between subjects factor (Lets say FactorA) with two levels: Big and Small and one within subjects factor (FactorB - Quality) with three levels: 1, 2 and 3 - corresponding to High, Medium and Low.

I want to examine the effect of both the factors on the Dependent Variable measured after each of the participant was put into one of the two conditions (Big or small) and evaluate some things (High, medium and low) : Dep_Var1, Dep_Var2 and Dep_Var3.

I am using the following code: 

proc glm data = Dataset.data;
class FactorA FactorB SubjectID;
model  Dep_Var1, Dep_Var2 Dep_Var3= FactorA|FactorB /ss3;
repeated SubjectID, FactorB;

lsmeans Condition/pdiff stderr;
run;

However I keep on getting the following statement in the Log:

NOTE: The CLASS variable FactorB has only one level: '1'.
ERROR: Ambiguous level information in REPEATED statement

Also if I change this to the following:

proc glm data = Dataset.data;
class FactorA FactorB SubjectID;
model  Dep_Var1, Dep_Var2 Dep_Var3= FactorA|FactorB /ss3;
repeated SubjectID;

lsmeans Condition/pdiff stderr;
run;

I get the following error: 

NOTE: The CLASS variable FactorB has only one level: '1'.
NOTE: H Matrix for SubjectID*FactorB has zero d.f.

NOTE: H Matrix for SubjectID*FactorA*FactorB has zero d.f.

Here's a snippet of the data for easy reference:

SubjectID	FactorA	Dep_Var1	Factor_B	Dep_Var2	Factor_B	Dep_Var3	Factor_B
1	Big	9	1	2	2	29	3
2	Small	9	1	5	2	28	3
3	Small	12	1	2	2	27	3
4	Small	9	1	2	2	28	3
5	Big	11	1	5	2	29	3
6	Big	9	1	5	2	21	3
7	Small	9	1	2	2	26	3
8	Big	10	1	2	2	26	3
9	Big	13	1	5	2	25	3
10	Small	10	1	4	2	25	3

I realize that I am making a mistake in how I have input FactorB, but cannot figure out what to do here. Any help is appreciated.

Thanks.

[pau13rown]

you need to restructure the dataset so factorb is listed downwards, rather than being split into 3 separate variables. The dataset snippet cannot be right though: you can't have 3 variables with the same variable name 'factorb'