Interpreting a MCMCglmm model with a bivariate response variable

Wed, Sep 23, 2015 7:38 AM

Hi,

a) Section 8 of the course notes details the use of 'triat'.

b) DIC is not implemented for multivariate threshold models. DIC, as  
its currently `focussed' is not useful anyway, I think.

Cheers,

Jarrod




The muklQuoting Iker Vaquero Alba <karraspito at yahoo.es> on Wed, 23 Sep  
2015 14:32:00 +0000 (UTC):

?? Hi, Jarrod and everyone else.
?? Thank you very much for your advise. Actually, I just realized  
after sending the email, I was going to send the correct one. The  
model:
testmodel1<-MCMCglmm(cbind(natapshort,nataplong)~gender+age+religion+sexor+selfattr+partnerattr+gender:age+gender:religion+gender:sexor+gender:selfattr+gender:partnerattr+age:religion+age:sexor+age:selfattr+age:partnerattr+religion:sexor+religion:selfattr+religion:partnerattr+sexor:selfattr+sexor:partnerattr+selfattr:partnerattr,random=NULL,rcov=~corg(trait):units,family=c("threshold","threshold"),data=extphen,nitt=100000,singular.ok=TRUE)
?And the summary outcome:
?summary(testmodel1)

?Iterations = 3001:99991
?Thinning interval? = 10
?Sample size? = 9700

?DIC:

?R-structure:? ~corg(trait):units

??????????????????????????? post.mean l-95% CI u-95% CI eff.samp
natapshort:natapshort.units??? 1.0000?? 1.0000?? 1.0000??????? 0
nataplong:natapshort.units???? 0.3469?? 0.2243?? 0.4744???? 7885
natapshort:nataplong.units???? 0.3469?? 0.2243?? 0.4744???? 7885
nataplong:nataplong.units????? 1.0000?? 1.0000?? 1.0000??????? 0

?Location effects: cbind(natapshort, nataplong) ~ gender + age +  
religion + sexor + selfattr + partnerattr + gender:age +  
gender:religion + gender:sexor + gender:selfattr +  
gender:partnerattr + age:religion + age:sexor + age:selfattr +  
age:partnerattr + religion:sexor + religion:selfattr +  
religion:partnerattr + sexor:selfattr + sexor:partnerattr +  
selfattr:partnerattr

?????????????????????? post.mean?? l-95% CI?? u-95% CI eff.samp?? pMCMC??
(Intercept)??????????? 3.170e+00 -1.940e+00? 8.301e+00???? 8794 0.21897??
genderM?????????????? -1.048e-01 -2.006e+00? 1.915e+00???? 9408 0.90948??
genderO?????????????? -5.316e+02 -1.827e+05? 1.854e+05???? 9864 0.99052??
age?????????????????? -1.006e+00 -3.414e+00? 1.266e+00???? 8847 0.39959??
religionY???????????? -2.823e+00 -5.121e+00 -5.111e-01???? 8322 0.01691 *
sexorHOM?????????????? 1.338e+03 -1.663e+05? 1.738e+05???? 9700 0.99608??
sexorOT??????????????? 8.310e+02 -1.580e+05? 1.586e+05???? 9700 0.99732??
selfattr????????????? -8.544e-01 -2.236e+00? 5.512e-01???? 9092 0.22454??
partnerattr??????????? 4.296e-01 -9.066e-01? 1.784e+00???? 8818 0.52598??
genderM:age??????????? 3.254e-02 -4.556e-01? 5.027e-01???? 9700 0.88557??
genderO:age??????????? 2.113e+02 -7.761e+04? 7.336e+04???? 9700 0.99918??
genderM:religionY???? -4.660e-01 -1.141e+00? 2.360e-01???? 9503 0.17258??
genderO:religionY????? 3.408e+02 -1.551e+05? 1.567e+05???? 9700 0.99485??
genderM:sexorHOM????? -7.522e-01 -1.687e+00? 1.528e-01???? 9700 0.11155??
genderO:sexorHOM?????? 8.643e+01 -1.468e+05? 1.512e+05???? 9700 0.99258??
genderM:sexorOT?????? -5.950e-01 -1.661e+00? 4.325e-01???? 9326 0.26742??
genderO:sexorOT??????? 6.955e+02 -1.589e+05? 1.664e+05???? 9700 0.99340??
genderM:selfattr?????? 3.038e-01 -1.054e-01? 6.976e-01???? 9334 0.13526??
genderO:selfattr????? -1.968e+02 -7.999e+04? 7.118e+04???? 9341 0.99340??
genderM:partnerattr?? -2.686e-01 -6.974e-01? 1.595e-01???? 9345 0.20866??
genderO:partnerattr??? 1.064e+00 -1.365e+00? 3.685e+00???? 8894 0.41155??
age:religionY????????? 3.473e-01 -3.822e-01? 1.100e+00???? 9215 0.34763??
age:sexorHOM????????? -6.704e+02 -8.690e+04? 8.316e+04???? 9700 0.99608??
age:sexorOT?????????? -4.160e+02 -7.930e+04? 7.899e+04???? 9700 0.99732??
age:selfattr?????????? 3.904e-01 -2.322e-01? 9.908e-01???? 9257 0.20351??
age:partnerattr?????? -5.805e-02 -6.213e-01? 5.200e-01???? 8974 0.85155??
religionY:sexorHOM???? 3.131e-01 -8.014e-01? 1.381e+00???? 9700 0.57505??
religionY:sexorOT???? -3.484e-03 -1.612e+00? 1.651e+00???? 7850 0.99278??
religionY:selfattr???? 1.074e-01 -3.688e-01? 5.790e-01???? 8506 0.65649??
religionY:partnerattr? 5.330e-01? 1.455e-01? 8.974e-01???? 8817 0.00495 **
sexorHOM:selfattr????? 3.787e-01 -3.850e-01? 1.134e+00???? 9101 0.31588??
sexorOT:selfattr?????? 3.805e-01 -2.086e-01? 9.754e-01???? 9163 0.20866??
sexorHOM:partnerattr?? 4.977e-01 -2.861e-01? 1.323e+00???? 8472 0.22639??
sexorOT:partnerattr?? -7.482e-02 -6.965e-01? 5.284e-01???? 9023 0.80000??
selfattr:partnerattr?? 5.051e-02 -1.438e-01? 2.540e-01???? 8700 0.62041??
---
Signif. codes:? 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1

?Cutpoints:
?????????????????????????? post.mean l-95% CI u-95% CI eff.samp
cutpoint.traitnatapshort.1???? 1.024?? 0.7313??? 1.335??? 872.3
cutpoint.traitnatapshort.2???? 2.362?? 2.0725??? 2.698??? 756.2
cutpoint.traitnatapshort.3???? 4.002?? 3.6299??? 4.396??? 884.4
cutpoint.traitnataplong.1????? 1.187?? 0.9010??? 1.489??? 828.4
cutpoint.traitnataplong.2????? 2.496?? 2.1718??? 2.812??? 727.6
cutpoint.traitnataplong.3????? 3.959?? 3.5890??? 4.350??? 872.9
Some additional questions, if that's fine:
1. Do I have to actually include the word 'trait' in the model,  
something like 'cbind(natapshort, nataplong) ~ trait + gender +  
age..."? What is the reason for that? Also, do I have to include  
interactions between 'trait' and other variables?
2. Why the summary of my model does not give me the DIC value? It  
appears empty.

Thank you very much.
Iker

__________________________________________________________________

?? Iker Vaquero-Alba
?? Visiting Postdoctoral Research Associate
?? Laboratory of Evolutionary Ecology of Adaptations
?? Joseph Banks Laboratories
?? School of Life Sciences
?? University of Lincoln?? Brayford Campus, Lincoln
?? LN6 7DL
?? United Kingdom

?? https://eric.exeter.ac.uk/repository/handle/10036/3381


      De: Jarrod Hadfield <j.hadfield at ed.ac.uk>
 Para: Iker Vaquero Alba <karraspito at yahoo.es>
CC: "r-sig-mixed-models at r-project.org" <r-sig-mixed-models at r-project.org>
 Enviado: Mi?rcoles 23 de septiembre de 2015 15:25
 Asunto: Re: [R-sig-ME] Interpreting a MCMCglmm model with a  
bivariate response variable

Hi Iker,

You need to follow the advice given to your previous post. With?
unconstrained residual variance the model is largely generating?
nonsense. Use `corg' instead of `us'. Also, depending on what the?
outcomes are you almost certainly need to have `trait' in the fixed?
effect specification.

Jarrod




? Quoting Iker Vaquero Alba <karraspito at yahoo.es> on Wed, 23 Sep 2015?
13:28:09 +0000 (UTC):




?? Hello all,
?? I am implementing a model with a multiple (bivariate) response?
variable using MCMCglmm. Both response variables and all the?
explanatory variables are categorical variables, with between 2 and?
6 levels. The model is as follows:
??
testmodel1<-MCMCglmm(cbind(natapshort,nataplong)~gender+age+religion+sexor+selfattr+partnerattr+gender:age+gender:religion+gender:sexor+gender:selfattr+gender:partnerattr+age:religion+age:sexor+age:selfattr+age:partnerattr+religion:sexor+religion:selfattr+religion:partnerattr+sexor:selfattr+sexor:partnerattr+selfattr:partnerattr,random=NULL,rcov=~us(trait):units,family=c("threshold","threshold"),data=extphen,nitt=100000,singular.ok=TRUE)
?? And this is the summary of the model after all the iterations:
??
summary(testmodel1)??Iterations =3001:99991?Thinninginterval? =?
10?Sample size? = 9700 ??DIC: ??R-structure:??
~us(trait):units????????????????????????????post.mean l-95% CI u-95%?
CI eff.sampnatapshort:natapshort.units??? 114108???992.1?? 213000????
7.105nataplong:natapshort.units????? 33245???310.8??? 66300????
4.656natapshort:nataplong.units ?????33245???310.8??? 66300????
4.656nataplong:nataplong.units?????? 82964???671.5?? 155869????
2.218??Location effects:cbind(natapshort, nataplong) ~ gender + age?
+ religion + sexor + selfattr +partnerattr + gender:age +?
gender:religion + gender:sexor + gender:selfattr +gender:partnerattr?
+ age:religion + age:sexor + age:selfattr + age:partnerattr+?
religion:sexor + religion:selfattr + religion:partnerattr +?
sexor:selfattr +sexor:partnerattr + selfattr:partnerattr?
???????????????????????post.mean? ?l-95% CI??u-95% CI eff.samp???
pMCMC?? (Intercept)???????????8.934e+02 -6.995e+02?2.596e+03???
275.73 0.22660?? genderM??????????????-8.936e+01 -7.437e+0
2?5.066e+02? 4236.67 0.75794?? genderO??????????????-1.292e+03?
-1.934e+05?1.765e+05? 9700.00 0.99052???
age??????????????????-3.493e+02 -1.170e+03?3.615e+02?? 505.92?
0.31918?? religionY????????????-7.361e+02 -1.598e+03?1.481e+01????
33.71 0.03402 * sexorHOM?????????????-1.235e+03?
-1.808e+05?1.679e+05? 9700.00 0.99814?? sexorOT??????????????
??2.193e+03 -1.589e+05? 1.687e+05 10583.09 0.97814???
selfattr?????????????-2.367e+02 -7.424e+02?1.706e+02?? 314.82?
0.24948?? partnerattr???????????1.391e+02 -2.667e+02?6.147e+02???
966.40 0.49546?? genderM:age???????????2.696e+01 -1.313e+02??
1.748e+02? 3786.10 0.69670?? genderO:age??????????-1.055e+04?
-8.325e+04?7.163e+04? 1722.63 0.78474???
genderM:religionY????-1.295e+02 -3.725e+02?8.194e+01?? 200.08?
0.20495?? genderO:religionY????-1.016e+04 -1.589e+05?1.505e+05??
8731.86 0.89052?? genderM:sexorHOM?????-2.245e+02?
-5.713e+02?4.443e+01?? 105.67 0.10495???
genderO:sexorHOM?????-8.104e+03 -1.620e+05?1.385e+05? 5318.22?
0.90474?? genderM:sexorOT??????-1.52
0e+02 -5.124e+02?1.856e+02?? 423.76 0.33402???
genderO:sexorOT???????2.628e+03 -1.654e+05?1.658e+05? 9700.00?
0.97670?? genderM:selfattr??????9.029e+01 -3.152e+01?2.334e+02???
119.78 0.12907?? genderO:selfattr??????6.281e+03?
-6.511e+04?8.524e+04? 3504.67 0.88412???
genderM:partnerattr??-7.284e+01 -2.160e+02?6.729e+01?? 263.29?
0.25052?? genderO:partnerattr???2.536e+02 -5.113e+02?1.121e+03??
1291.76 0.49113?? age:religionY?????????8.732e+01?
-1.283e+02?3.457e+02?? 727.46 0.42289???
age:sexorHOM??????????2.809e+02 -8.592e+04?8.847e+04? 9700.00?
0.99711?? age:sexorOT??????????-1.246e+03 -8.447e+04?7.941e+04??
9370.57 0.97526?? age:selfattr??????????1.195e+02?
-6.636e+01?3.452e+02?? 212.35 0.19567???
age:partnerattr??????-8.598e+00 -1.963e+02?1.714e+02? 9700.00?
0.92227?? religionY:sexorHOM????8.506e+01 -2.392e+02?4.612e+02??
2059.92 0.59959?? religionY:sexorOT?????1.420e+01?
-5.170e+02?5.464e+02? 9700.00 0.96268???
religionY:selfattr????2.782e+01 -1.198e+02?1.833e+02? 3520.80?
0.68701?? religionY:part
nerattr?1.407e+02? 1.423e+01? 2.886e+02???22.99 0.00928?
**sexorHOM:selfattr?????1.160e+02 -1.141e+02?3.707e+02?? 394.74?
0.28495?? sexorOT:selfattr??????1.006e+02 -8.528e+01?3.050e+02???
305.50 0.24577?? sexorHOM:partnerattr??1.231e+02?
-1.246e+02?3.990e+02?? 415.43 0.31072???
sexorOT:partnerattr??-1.401e+00 -2.007e+02 ?1.956e+02?9700.00?
0.99237?? selfattr:partnerattr??5.483e+00 -6.017e+01?7.207e+01??
3007.45 0.85464?? ---Signif. codes:? 0?***? 0.001 ?**? 0.01 ?*? 0.05?
?.? 0.1 ? ? 1??Cutpoints: ??????????????????????????post.mean l-95%?
CI u-95% CI eff.sampcutpoint.traitnatapshort.1???? 235.2???62.34????
376.2??? 8.822cutpoint.traitnatapshort.2???? 633.4??202.16????
944.0??? 3.578cutpoint.traitnatapshort.3???1139.5?? 364.35???
1683.7???5.832cutpoint.traitnataplong.1????? 293.4???54.85????
433.7??? 5.203cutpoint.traitnataplong.2????? 651.8??223.70????
961.6??? 2.604cutpoint.traitnataplong.3????1023.1?? 344.82???
1483.0???2.353
??
So, my question is: in that summary, where are the effect sizes, are?
they the "post. mean" column? And have they been transformed in some?
way? Because obviously, for response variables that can only take?
values 1,2,3,4 or 5, I would expect to see those as the effect size.
Also, is there any way of knowing to what extent are those results?
due to each specific response variable, and the degree of covariance?
between both? Is it possible to get all that information from that?
summary output I have copied above?
?? Thank you very much.?? Iker

__________________________________________________________________

?? Iker Vaquero-Alba
?? Visiting Postdoctoral Research Associate
?? Laboratory of Evolutionary Ecology of Adaptations
?? Joseph Banks Laboratories
?? School of Life Sciences
?? University of Lincoln?? Brayford Campus, Lincoln
?? LN6 7DL
?? United Kingdom

?? https://eric.exeter.ac.uk/repository/handle/10036/3381


??? [[alternative HTML version deleted]]

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Interpreting a MCMCglmm model with a bivariate response variable

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