[R-sig-ME] MCMCglmm predict function output and interpretation

[Jarrod Hadfield]

Hi Justine,

If you get the predictions on the link scale, and denote these as  
eta_1 and  and eta_635 for the first observation, then

Pr(A) = 1/(1+exp(eta_1)+exp(eta_635))
Pr(B) = exp(eta_1)/(1+exp(eta_1)+exp(eta_635))
Pr(C) = exp(eta_635)/(1+exp(eta_1)+exp(eta_635))

There is some code for doing this (and marginalising any random  
effects) in the CourseNotes (p97 after Eq. 5.7).

Cheers,

Jarrod


Quoting Justine <jsmith5 at ucsc.edu> on Mon, 28 Jul 2014 23:45:09 +0000 (UTC):

> Jarrod Hadfield <j.hadfield at ...> writes:
>
>>
>> Hi Justine,
>>
>> The first 634 predictions are for B vs A, and the second 634 are for C
>> vs A. If you want the predicted probabilities of falling in category
>> A, B or C you'll have to do it by hand I'm afraid.
>>
>> Cheers,
>>
>> Jarrod
>>
>
> Hi Jarrod,
>
> Thanks so much for clearing that up. Just to make sure I'm absolutely clear,
> if column 1 is 0.228, and column 635 is 0.092, than for data point #1 the
> probability option B is more likely than option A is 0.228 and C more likely
> than A is 0.092? Does this indicate that A (the reference value) is the most
> likely? Can I calculate its relative probability by subtracting the other
> two values from 1? I'm happy to assign the categories by hand, but I want to
> make sure I am interpreting the output correctly.
>
> Thanks again,
>
> Justine
>
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