I want to test which factor is more significant in explaining the data. Also, I want to test whether there is an interaction or not.
It is not a crossed design because every level of one factor does not occur in all levels of the other. eg B1 does not occur in level A3. However, this is not a nested design either because A1 does not contain B1 without A2 containing B1. Likewise, B1 does not contain A2 without B2 containing A2.
A<-gl(3,2) #factor of 3 levels B<-gl(2,3) #factor of 2 levels y<-rnorm(6,10) #response df<-data.frame(y,A,B,x) df y A B 1 11.944285 1 1 2 10.058154 1 1 3 10.618764 2 1 4 10.928283 2 2 5 10.286781 3 2 6 9.695895 3 2
I am guessing that there is something wrong with this experiment. What is wrong with this design?