Hello,
I have an experiment of split-plot design with :
Main plot factor: Rootstock Genotypes (US-802, US-812, US-897, Cleopatra, Swingle, US-1516, US-942, X639)
Subplot factor: Methods of propagation (cutting, seedling, Tissue culture)
Dependent variables: Plant height, Canopy thickness, rootstock diameter, Scion diameter
The problem is not all the treatments are available.
For instance, I have Rootstock genotype US-802, which has the Cutting and Seedling method of propagation but not the tissue culture method. ( I have attached a picture that shows which of the combinations are not available)
Could anyone suggest to me how can the data be analyzed in such a case?
Is it good to do the ANOVA test assuming that the design is complete?
Yes, you can use a split plot ANOVA to analyse the level of information that you do have. Forget the culture method if you don't have the data!
I mean I have the data for both factors. Its just that not all the combination of factors are available. You can please have a look at the picture attached that shows what combinations are not available.
When planning such an experiment, I would make a list of all the treatment combinations you do have.? Then clearly specify your research question?
What are you measuring, how many replicates do you need? (from a sample size calculation). try to write out the experiment- as your diagram does not clearly show the actual experimental layout- with randomisation etc.
are the Genotypes all one one species ?
What are you measuring ?
probably best to describe the experiment as treatment combinations, and 18 replicates of each. Are you using Blocks - where you replicate the species within a glasshouse or field. using a block to reduce variability, and to take into account any environmental gradients. ce etc)
With a one-way anova with all the treatment combinations (that you have0. You could look within the treatments as a pre-planned comparison.
(eg compare a method within a rootstock). It is always good to need to seek advise from a statistician, before you start.
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