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Dear All,I have a question regarding data transformation for further multivariative analysis.I would like to do a RDA analysis to check how environmental variables affect water quality. Before analysis I checked the data and found that some data are very skewed and in order to make data achieve normality and homogenity of variance different kinds of data-transformation are suitable (e.g. in some case log-transformation, while in another - square root transfromation). I would like to ask whether it is possible to apply such different kinds of transformation for data and then use in RDA? Or the same transformations (if applied) should be applied for all data? Are there any references for this?I will be very thankful for your reply. Thanks in advance!Best wishes,Oleksandra
I think these transformations are relevant and essential for the X data matrix, but less for the Y data matrix, which is basically a contingency table.
Best of luck
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