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How to display p-values adjusted across multiple groups of comparisons with pwpp()? #472
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I think as it is currently designed, I suppose it is technically possible to do this, but I'm having trouble thinking of what kind of argument to provide. Thinking out loud, maybe it's possible to provide an object that already has the comparisons you want, such as
and maybe then have something like
But this is pretty shaky because we can't get the coefs directly:
The coefs are nulled-out when we do the Let me ponder this for a while. |
I figured out how to do what you want. Note that the result of
if we exclude the first two columns, we have a named list of contrast coefficients. Thus, just use them as the contrast method (we have to null-out the
|
I have a less-hacky way to do this. Note that we can get the combined groups by using the
So, one would hope that
would work right. However, it doesn't, because |
Hi Russ this is excellent. I would be curious if there is a way to get the
|
Well, I see that the I believe that the rendering issues in the second one are due to the fact that the line segments are rendered in two parts with a color change halfway between, and the midpoints of those segments don't get included in the grouping as far as scaling is concerned. Offhand, I am not sure that can be fixed, just because in general, the midpoints can be associated with more than one level of a given factor. |
Yes, it was just that the extra labels occur in each panel but it's not a huge issue. Thanks so much for working on it! |
The issue with |
Hi Russ, I appreciate your great documentation on comparisons, in particular your answer on this stackexchange post about how to define the family for multiple comparisons correction differently than the groups within which the pairwise comparisons are done.
My question is how to interact this with a plot generated with
pwpp()
. I have two interacting factors and want to do pairwise comparisons of factor A levels within each level of factor B. But I want to use FDR correction across all comparisons done in this way. For example if there are 3 levels of factor A and 100 levels of factor B, that's 3 pairwise comparisons within each of 100 groups for a total of 300 comparisons.I have no problem doing this to display in a table, as in this example:
However with a
pwpp()
plot it only does the FDR adjustment within each Date group which is correcting for fewer comparisons than I want it to. If I switchpwpp()
toby = NULL
this is also not correct because it now does every possible comparison of combinations of Variety and Date, instead of just the Variety comparisons within each Date.Thanks in advance for your help!
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