----Messaggio originale----
Da: j.hadfield at ed.ac.uk
Data: 24/08/2011 18.11
A: "m.fenati at libero.it"<m.fenati at libero.it>
Cc: <r-sig-mixed-models at r-project.org>
Ogg: Re: [R-sig-ME] pMCMC and HPD in MCMCglmm
Hi,
pMCMC is the two times the smaller of the two quantities: MCMC
estimates of i) the probability that a<0 or ii) the probability that
a>0, where a is the parameter value. Its not a p-value as such, and
better ways of obtaining Bayesian p-values exist.
HPDinterval finds the closest points (c and d) for which Fa(d)-Fa(c) =
0.95 (If prob=0.95 in HPDinterval) and Fa is the empirical cumulative
distribution of a.
Cheers,
Jarrod
On 24 Aug 2011, at 16:14, m.fenati at libero.it wrote:
Hi Jarrod,
thanks for your answer, but I have again a lot of confusion. If
possible,
could you explain to me the definition of pMCMC?
Maybe, knowing the right definition of pMCMC I will be able to
understand
completely your answer.
Thank a lot!
Massimo
-----------------------
Massimo Fenati
DVM
Padova - Italy
----Messaggio originale----
Da: j.hadfield at ed.ac.uk
Data: 24/08/2011 13.24
A: "m.fenati at libero.it"<m.fenati at libero.it>
Cc: <ndjido at gmail.com>, <r-sig-mixed-models at r-project.org>
Ogg: Re: [R-sig-ME] pMCMC and HPD in MCMCglmm
Hi Massimo,
They only need to be slightly skewed (even up to Monte Carlo error
probably) - conclusions drawn from HPDinterval and pMCMC are in
reality almost identical in your example, it is the consequences of
the (arbitrary) distinction between <0.05 and >0.05 that makes them
"feel" different. Lets say we used the cutoff <0.06 and >0.06. Does
HPDinterval(m1$Sol[,3], prob=0.94) overlap zero? If not then
HPDinterval and pMCMC "agree" with respect to which side of the
cutoff
the probability lies ? It may make us happier, but it shouldn't.
Jarrod
On 24 Aug 2011, at 11:45, m.fenati at libero.it wrote:
The posterior distribution seem to be only slightly skewed.
However the question remains: what is the sense of the discrepancy
between HPD
and pMCMC?
Thanks
Massimo
----Messaggio originale----
Da: ndjido at gmail.com
Data: 24/08/2011 11.43
A: "m.fenati at libero.it"<m.fenati at libero.it>
Cc: <r-sig-mixed-models at r-project.org>
Ogg: Re: [R-sig-ME] pMCMC and HPD in MCMCglmm
Check your posterior distributions, the one corresponding to GENDER
seems to
be skewed.
Ardo.
On Wed, Aug 24, 2011 at 11:33 AM, m.fenati at libero.it <m.fenati at libero.it
wrote:
As suggested by Ben Bolker, I re-post the following question in this
list.
Thanks
Dear R users,
I?d like to pose aquestion about pMCMC and HDP.
I have performed a mixed logistic regression by MCMCglmm (a very
good
obtaining the following results:
Iterations = 250001:799901
Thinning interval = 100
Sample size = 5500
DIC: 10.17416
G-structure: ~ID_an
post.mean l-95% CI u-95% CIeff.samp
ID_an 0.7023 0.0001367 3.678 2126
R-structure: ~units
post.mean l-95% CIu-95% CI eff.samp
units 1 1 1 0
Location effects: febbreq~ as.factor(sex)
post.mean l-95% CIu-95% CI eff.samp pMCMC
(Intercept) -3.6332 -5.6136 -1.7719 3045 <2e-04 ***
as.factor(sex)M -2.9959 -6.0690 0.1969 2628 0.0455 *
---
Signif. codes: 0 ?***?0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
As you can see, pMCMC for gender is just less than 5%, but the
credible
interval (HPD) is wide and includes the 0 value.
How can I interpret these different results?
Thank you in advance
Massimo
-----------------------
Massimo Fenati
DVM
Padova - Italy