[R-sig-ME] predictions for MCMCglmm

[Jarrod Hadfield]

cc-ing back to the list ...

Hi,

Yes you can do it that way, and it should give the same answer.  It  
will slow down the MCMCing in terms of time per iteration and mixing  
though.

Cheers,

Jarrod


Quoting "Antonio P. Ramos" <ramos.grad.student at gmail.com> on Thu, 21  
Mar 2013 18:18:41 -0700:

>  Hi all,
>
> I have a follow up question: what is different between getting predictions
> used this code - which works fine - or, instead, by adding rows in the data
> matrix with NA values in the response and the desired covariates in the X
> matrix, such as often done by people using JAGS/BUGS? I am not sure at all,
> but it seems to be that by running this code, I am assuming that the
> predictions I want have some kind of random structure that might not be the
> case - by marginalizing over them all. Thanks for any further
> clarification. Antonio Pedro.
>
>
> On Tue, Mar 19, 2013 at 11:35 AM, Antonio P. Ramos <
> ramos.grad.student at gmail.com> wrote:
>
>> sorry: the full code here
>> > pred.data.pred <-
>> data.frame(maternal_age_c=rep(20,25),wealth=rep("Lowest quintile",25),
>> +
>>  birth_year=1971:1995,birth_order=rep(1,25),
>> +
>>  sex=rep("Female",25),residence=rep("Rural",25),
>> +                                    maternal_educ=rep("Primary",25))
>> > # creating predictions "by hand"
>> > X <- model.matrix(~ maternal_age_c + I(maternal_age_c^2)  +
>> as.factor(birth_year) +
>> +                   as.factor(birth_order) + residence + sex + wealth,
>> data=pred.data.pred)
>> Error in `contrasts<-`(`*tmp*`, value = contr.funs[1 + isOF[nn]]) :
>>   contrasts can be applied only to factors with 2 or more levels
>>
>>
>>
>>
>> On Tue, Mar 19, 2013 at 11:35 AM, Antonio P. Ramos <
>> ramos.grad.student at gmail.com> wrote:
>>
>>> Thanks for you reply Jarrod. The problem is that model.matrix doesn't
>>> allow me to created the predication I need as factors cannot have just one
>>> level. Any ways around data? thanks a bunch
>>>
>>>
>>> pred.data.pred <- data.frame(maternal_age_c=rep(20,25),wealth=rep("Lowest
>>> quintile",25),
>>>
>>>  birth_year=1971:1995,birth_order=rep(1,25),
>>>
>>>  sex=rep("Female",25),residence=rep("Rural",25),
>>>                                    maternal_educ=rep("Primary",25))
>>> # creating predictions "by hand"
>>> X <- model.matrix(~ maternal_age_c + I(maternal_age_c^2)  +
>>> as.factor(birth_year) +
>>>                   as.factor(birth_order) + residence + sex + wealth,
>>> data=pred.data.pred)
>>>
>>>
>>>
>>> On Tue, Mar 19, 2013 at 2:27 AM, Jarrod Hadfield  
>>> <j.hadfield at ed.ac.uk>wrote:
>>>
>>>> Hi Antonio,
>>>>
>>>> With (simple) random effects marginalised:
>>>>
>>>> X<-model.matrix(~ maternal_age_c + I(maternal_age_c^2)  +
>>>> as.factor(birth_year) + residence + sex + wealth, data=newdata)
>>>>
>>>> V<-rowSums(glm.MC.2$VCV)
>>>>
>>>> beta<-glm.MC.2$Sol
>>>>
>>>> c2 <- (16 * sqrt(3)/(15 * pi))^2
>>>>
>>>> pred<-t(plogis(t(beta%*%t(X)/**sqrt(1+c2*V))))
>>>>
>>>> pred[i,j] is the prediction for the jth new data point for the ith MCMC
>>>> sample. colSums(pred)  should be equivalent to the output from
>>>> predict.MCMCglmm.
>>>>
>>>> Cheers,
>>>>
>>>> Jarrod
>>>>
>>>>
>>>>
>>>>
>>>> Quoting "Antonio P. Ramos" <ramos.grad.student at gmail.com> on Mon, 18
>>>> Mar 2013 20:04:07 -0700:
>>>>
>>>>  Hi all.
>>>>>
>>>>> As far as I can tell newdata is still not implemented for this nice
>>>>> package. Thus I wonder what would be the best way to get predictions "by
>>>>> hand". My model is actually very simple. Still I need to marginalize the
>>>>> random effects. Any hints? Thanks in advance, Antonio Pedro.
>>>>>
>>>>>
>>>>> glm.MC.2 <- MCMCglmm(mortality.under.2 ~ maternal_age_c +
>>>>> I(maternal_age_c^2)  +
>>>>>                        as.factor(birth_year) + residence +
>>>>>                        sex + wealth,
>>>>>                      nitt=20000, thin=10, burnin=1000,
>>>>>                      random= ~CASEID, prior=prior.2,data=egypt2,
>>>>> family='categorical')
>>>>>
>>>>>         [[alternative HTML version deleted]]
>>>>>
>>>>> ______________________________**_________________
>>>>> R-sig-mixed-models at r-project.**org  
>>>>> <R-sig-mixed-models at r-project.org>mailing list
>>>>> https://stat.ethz.ch/mailman/**listinfo/r-sig-mixed-models<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.
>>>>
>>>>
>>>>
>>>
>>
>



-- 
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.