[R-sig-ME] MCMCglmm: Question about posterior mean.

[Iker Vaquero Alba]

Hello everyone,Just a quick question: Could we somehow interpret posterior mean in an MCMCgklmm summary (see below) as kind of an effect size of each predictor? I mean, for example, the intercept for "appcareshort" (score from 1 to 5 given by participants in a survey to the attractiveness in a potential partner of appearance care for a short, casual relationship) is 3.242. So, is, for example, the effect of gender M on "appcareshort" more negative than the intercept? Or in other words, do male participants in the survey value care of appearance in potential partners significantly less than people of other gender?
  
                                         post.mean   l-95% CI   u-95% CI  eff.samp  pMCMC    traitappcareshort                        3.242e+00 -3.209e+00  9.638e+00  9201.037 0.3247    traitappcarelong                         3.700e+00 -2.789e+00  1.034e+01  8610.520 0.2625    traitappcareshort:genderM               -1.128e-01 -2.526e+00  2.356e+00  9113.094 0.009**    traitappcarelong:genderM                 1.273e-01 -2.270e+00  2.663e+00  8641.121 0.9243    traitappcareshort:genderO                1.005e+03 -1.787e+05  1.873e+05  9700.000 0.9872    traitappcarelong:genderO                -2.177e+03 -1.895e+05  1.855e+05 10368.220 0.9839    traitappcareshort:age                   -7.331e-01 -3.681e+00  2.267e+00 10202.025 0.6200    traitappcarelong:age                    -1.433e+00 -4.507e+00  1.571e+00  8834.924 0.3546    traitappcareshort:religionY             -2.229e+00 -5.144e+00  6.142e-01  9157.812 0.1214    

Also: as far as I can understand, the effective sample size is the number of iterations that MCMCglmm actually stores, and from which it "constructs" the posterior distribution. In this case, the total number of iterations was 100,000 and effective sample was always around 10,000 (which makes sense given that thin=10). My doubt is in that predictor with an effective sample size of 1.404. My experience tells me that when I plot the model for diagnostic purposes, that very predictor is going to show a clear lack of convergence. I would just like to ask whether I am right in what effective sample size means, what is the difference between the sample size (9700) and the effective sample size of the predictors, and how it's possible an effective sample size of 10,368 with 100,000 iterations and thin=10.

Thank you very much in advance to everyone.

Kind regards,
Iker  
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