Hello list members,
this is rather a simple question but I can't find the solution myself, so I
would appreciate your help and I apologise in advance for my ignorance.
I have a data frame with a header containing variable names and I have 4
independent variables and 5 dependent variables. It looks like this:
x1 x2 x3 x4 y1 y2 y3 y4 y5
1 1 33 55 4 0.3 0.38 1.55 30.1
1 1 52 56 5.5 0.28 0.36 1.51 20.8
1 1 72 55 7.9 0.27 0.36 1.52 15.1
1 2 33 34 4.7 0.34 0.41 1.55 23.2
..............
and it contains a few more data points. I want to estimate the significance
of the independent variables on each of the dependent but not all the
independent variables are random factors. x1 is a category (qualitative)
taking 2 values, x2 and x3 are quantitative fixed-effects factors with 3
levels and x4 is a random factor highly correlated with x3 (so for
simplicity, I am thinking of skipping one of these 2 factors from the
analysis). Furthermore, there is no replication, so I have to estimate the
experimental error in terms of the higher-order interactions.
I tried the aov( ) function with a model like y2~x1*x2*x3+Error(x1:x2:x3).
The result I got was different from what the Statistica (ANOVA with
fixed-effects model and customised error term) is producing. I suspect that
the difference arises from the fact that I have to define somehow the nature
of the dependent variables otherwise they are treated as random quantitative
factors. I couldn't find a relevant example in the manuals. Can somebody
provide some help?
Thanks in advance.
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