For example, I do ADONIS (http://cc.oulu.fi/~jarioksa/softhelp/vegan/html/adonis.html) to investigate an effect of BMI (continues variable) on beta-diversity (weighted UniFrac) and I got significant p-value. This means that BMI have an effect on beta-diversity. How the p-value was calculated?
H0 for ADONIS is ‘‘the centroids of the groups, as defined in the space of the chosen resemblance measure, are equivalent for all groups.’’. It’s pretty clear how this hypothesis will be tested when having two groups. But it is not clear how this is done in case of continues variable. Does anyone know?
One more question :), I often see that PERMANOVA and ADONIS are used interchangeably. Is this correct?
I contact the author of this page http://cc.oulu.fi/~jarioksa/softhelp/vegan/html/adonis.html
and the answer is:
"Good question. I should probably change that definition. Variation explained is directly analogous to that of general linear models. With a continuous variable, it acts like simple linear regression, where each point is associated with its own "centroid" which is the best fit linear approximation." Now everything makes sense.
Do you know how to check for model assumptions when using continuous variable in adonis2() function? For comparing groups you first need to test whether the variance (dispersion) is equal, and only if it's equal you can test community differences with adonis2() - but how do you check for this when using continuous variables?
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