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dsuchoff
Calcite | Level 5

My apologies for the somewhat convoluted title. Let me explain:

 

We are conducting a greenhouse study in which we are looking at plant genotype (factor A) and irrigation (factor B). Plants are grown in pots to which we randomly assigned both genotype and irrigation. The study is a full factorial RCBD with five blocks. In analyzing the data, I notice that the effect of irrigation is very strong, and I wonder if the variability associated with it overshadows potential interactions? Here is an example of analyzed data for stomatal conductance in which we took two subsamples per plant.

 

 SAS Output

 

  SAS Output
Type III Tests of Fixed Effects


Effect    Num DF    Den DF     F Value       Pr > F
   Genotype   2       50               3.06         0.0559

Irrigation    1       50      1168.62         <.0001
  Interaction   2      50              1.97           0.1506

 

Any input would be much appreciated!

 

 

David 

1 ACCEPTED SOLUTION

Accepted Solutions
PaigeMiller
Diamond | Level 26

If you truly have a full factorial, then the answer to your question is NO. Each factor and interaction explains a certain amount of variability of the response, independently of the others, and so the big value you get is because the effect of irrigation is huge, and the effect of genotype and interaction is quite small.

--
Paige Miller

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3 REPLIES 3
PaigeMiller
Diamond | Level 26

If you truly have a full factorial, then the answer to your question is NO. Each factor and interaction explains a certain amount of variability of the response, independently of the others, and so the big value you get is because the effect of irrigation is huge, and the effect of genotype and interaction is quite small.

--
Paige Miller
dsuchoff
Calcite | Level 5
Thank you, Paige. That's what I was thinking, but wanted more expert advice.
Thanks again.
Rick_SAS
SAS Super FREQ

That's the beauty of designed experiments: the factors are not correlated

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