Message-ID: <20314081.8948631314178380645.JavaMail.defaultUser@defaultHost>
Date: 2011-08-24T09:33:00Z
From: m.fenati at libero.it
Subject: pMCMC and HPD in MCMCglmm
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
package)
>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