I have conducted one experiment involving 2 levels of compost as basal fertilization and 3 levels of liquid fertilizer as topdressing fertilization plus 1 control using conventional chemical fertilizers.
It seems to be a factorial 2*3 + 1 control, totaled 7 treatments, each replicates 3 times.
Can I simply subject 7 treatments into one-way ANOVA for the mean comparison?
Or should I run two-way ANOVA (2*3) for the factorial combinations first, then compare the control with each other 6 treatments later?
Thank you very much for your kind recommendation.
In such cases (context of the main question of the discussion thread), the two-way ANOVA should precede the one-way ANOVA in order to detect possible interactions between the factors on the response variable/s.
You should use RCB Design for all the 7 treatments. Then for the means separation,it depends on what you have in mind. Are you looking for the best among the 7 treatments? Or are you looking for a treatmentamongthe 6 that can be as good as the control?
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Thank you very much all of you for the answers.
Dr Abba Nabayi , I used RCBD for all the 7 treatments as you said.
My main targets are to evaluate the best combination of the factorial 2*3, and then compare them all to the control as a conventional practice to suggest the most suitable alternative fertilization using the compost and the liquid fertilizer.
Prof. Aristidis Matsoukis , thank you very much for your suggestion. I planned to do 2-way ANOVA for the factorial 2*3 to evaluate the main effects or interactions there, before one-way ANOVA for 7 treatments to compare the 6 with the control.
I just wonder if only one-way ANOVA is enough as said by Dr Vipin Borole .
Thank you all very much.
An experimental design and analysis which address a specific question robustly and give a practically useful answer matter.
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