Hello to all,
reading some scientific articles I came across experiments conducted with orthogonal designs. I think I have sensed its great potential, especially regarding the reduction of samples.
It seems that many authors use these designs to rank the different factors (decided a priori) that influence a certain response variable. For example, I might want to evaluate how temperature (20.25.30 ° C), a different type of soil (clayey, sandy and silty) and a fertilizer (A, B, C) influence the microbial respiration of the soil.
I have seen that many authors generate the drawing (and there are programs like SPSS that do it automatically), then they draw up a classification 8ranking) of these factors (for example the temperature and the factor that least influences breathing while the fertilizer is the one that has the greatest effect), then some report that the differences are calculated with ANOVA, but how is it possible to conduct a test with such an experimental design? I don't have the "classic repetitions" and this thing confuses me...
This article may help you:
http://en.cnki.com.cn/Article_en/CJFDTotal-SYJL201009019.htm
Thank you for sharing this Jonathan Ben Avraham . Unfortunately, it seems that I do not have access to it. In case you have access, would you mind sending me a private copy?
Thank you
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