Ahh, I was using type="response" not "terms. Thanks!


On Tue, Jul 29, 2014 at 12:04 PM, Jarrod Hadfield <j.hadfield@ed.ac.uk>
wrote:

> Hi Justine,
>
> eta_1 and eta_635 can be negative. If you make them both -10 for example,
> then Pr(A) is close to one.
>
> jarrid
>
>
>
> Quoting Justine Smith <jsmith5@ucsc.edu> on Tue, 29 Jul 2014 10:55:28
> -0700:
>
>  Hi Jarrod,
>>
>> This is great. I have one final question: using the above equations, I am
>> finding it impossible for Pr(A) to ever be the greatest (in fact, Pr(C )
>> is
>> always largest using my data set). Even if I put in tiny values for eta_1
>> and eta_635 (0.0001 and 0.0001), all values just become essentially equal.
>> See results from some made-up combinations below:
>>
>>
>>   eta_1 eta_635 Pr (A)  Pr (B) Pr (C )  0.0001 0.0001 0.333311111
>> 0.333344444 0.333344444  0.0001 0.5 0.274061108 0.274088515 0.451850377
>>  0.5
>> 0.0001 0.274061108 0.451850377 0.274088515
>>
>> Why would this be the case? I know from the data that A is in fact the
>> most
>> common outcome.
>>
>> Best,
>> Justine
>>
>>
>>
>> On Tue, Jul 29, 2014 at 1:38 AM, Jarrod Hadfield <j.hadfield@ed.ac.uk>
>> wrote:
>>
>>  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@ucsc.edu> on Mon, 28 Jul 2014 23:45:09 +0000
>>> (UTC):
>>>
>>>  Jarrod Hadfield <j.hadfield@...> 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
>>>>
>>>> _______________________________________________
>>>> R-sig-mixed-models@r-project.org mailing list
>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>>>
>>>>
>>>>
>>>>
>>>
>>> --
>>> The University of Edinburgh is a charitable body, registered in
>>> Scotland, with registration number SC005336.
>>>
>>>
>>>
>>>
>>
>> --
>> Justine A. Smith
>> PhD Student
>> Department of Environmental Studies
>> University of California, Santa Cruz
>> 1156 High St.
>> Santa Cruz, CA 95064
>> people.ucsc.edu/~jsmith5
>> santacruzpumas.org
>> conservationscats.com
>>
>>
>
>
> --
> The University of Edinburgh is a charitable body, registered in
> Scotland, with registration number SC005336.
>
>
>


-- 
Justine A. Smith
PhD Student
Department of Environmental Studies
University of California, Santa Cruz
1156 High St.
Santa Cruz, CA 95064
people.ucsc.edu/~jsmith5
santacruzpumas.org
conservationscats.com

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