I have data from my bioassay study (pot, field and GC-MS) and want to publish paper in impact factor journals. Which type of statistical method can increase my paper quality and chances of acceptance.
I think the best way to get your paper accepted in a Journal with impact factor is to use multivariate analysis. If you are using GC/MS data obtained on pot and field experiments, then you must have data from a lot of variables. Which factors did you use in your experimental design?
Different doses of two herbicides at three times of application in field and Doses, soil textures and incubation periods in pot study.
I imagine that you are using variables related to the pesticide residues and some variables related to weed
presence and physiological variables that inform about how the crop is responding to the treatments. I suggest you to analyze firstly the pot and field experiments separately. All your response variables can be included in a PCA analysis. You must designate all your investigated objects (treatments) by a code and you should only include the average of all replications for the statistical analysis. The distribution of objects in the score plot will tell you about associations between treatments and you can make judgments about the importance of each factor studied on the systematic variation of all your response variables. The interpretation of score and loading plots together will tell you about which treatments generate higher or lower values of response variables. You can do the same for the pot experiment with the three factors you mentioned.
I do not know if you are interested into make any kind of prediction.
I suggest you to find the book:
Esbensen, K.H.; Guyot, D.; Westad, F.; Hoummøler, L.P. Multivariate data analysis in practice. An introduction to multivariate data analysis and experimental design. 5th Ed. 2003. CAMO Process AS, 587 pp.
I hope this can help.
Regards, Amaury
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