Hello, I'm running this ordered category outcome model:
glme5.very.len <- MCMCglmm(very.len.summative.o ~ 1 ,
prior=list(R=list(V=1, fix=1), G=list(G1=list(V=1,
nu=0), G2=list(V=1, nu=0), G3=list(V=1, nu=0), G4=list(V=1, nu=0) )),
random = ~emplid + deptid + grade.f + subject.f ,
family = "ordinal",
nitt=300000,
data = summative.ratings.prin.yr1.full)
I ran it first with nitt=100000 but had very high autocorrelations and
non-sensical variance components and fixed effects, so I increased nitt
to 200000 and then to 300000 but got no change. Here's the summary
output:
summary(glme5.very.len)
Iterations = 3001:299991
Thinning interval = 10
Sample size = 29700
DIC: -13239.32
G-structure: ~emplid
post.mean l-95% CI u-95% CI eff.samp
emplid 405.3 1.493e-11 1106 7.909
~deptid
post.mean l-95% CI u-95% CI eff.samp
deptid 131.8 1.118e-16 475.2 42.65
~grade.f
post.mean l-95% CI u-95% CI eff.samp
grade.f 0.9143 1.405e-17 1.575 15784
~subject.f
post.mean l-95% CI u-95% CI eff.samp
subject.f 1.633 1.951e-17 2.748 10101
R-structure: ~units
post.mean l-95% CI u-95% CI eff.samp
units 1 1 1 0
Location effects: very.len.summative.o ~ 1
post.mean l-95% CI u-95% CI eff.samp pMCMC
(Intercept) 29.007 2.091 54.969 2.381 <3e-05 ***
---
Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
Cutpoints:
post.mean l-95% CI u-95% CI eff.samp
cutpoint.traitvery.len.summative.o.1 14.06 0.8102 27.38 9.382
cutpoint.traitvery.len.summative.o.2 40.34 2.9611 76.04 2.694
Here are some of the autocorrs:
autocorr(glme5.very.len$VCV)
, , emplid
emplid deptid grade.f subject.f units
Lag 0 1.0000000 0.5860851 0.04668197 0.06081864 NaN
Lag 10 0.9514313 0.6132116 0.04345287 0.05652945 NaN
Lag 50 0.9459831 0.6259477 0.04881253 0.06093640 NaN
Lag 100 0.9433509 0.6282599 0.04492884 0.06037288 NaN
Lag 500 0.9267886 0.6373151 0.03873992 0.05371885 NaN
, , deptid
emplid deptid grade.f subject.f units
Lag 0 0.5860851 1.0000000 0.03070680 0.03453008 NaN
Lag 10 0.6137187 0.7579551 0.03233992 0.04139315 NaN
Lag 50 0.6255810 0.7169468 0.02903334 0.03960446 NaN
Lag 100 0.6269979 0.7029498 0.03244468 0.04857241 NaN
Lag 500 0.6322900 0.6650247 0.04049514 0.04306019 NaN
Is there a problem in my data or in the model?
Thank you.
--
Stuart Luppescu -=- slu .at. ccsr.uchicago.edu
University of Chicago -=- CCSR
???????? -=- Kernel 3.2.1-gentoo-r2
Benjamin Lloyd-Hughes: Has anyone had any joy
getting the rgdal package to compile under
<windows? Roger Bivand: The closest anyone has got
so far is Hisaji Ono, who used MSYS
(http://www.mingw.org/) to build PROJ.4 and GDAL
(GDAL depends on PROJ.4, PROJ.4 needs a PATH to
metadata files for projection and transformation),
and then hand-pasted the paths to the GDAL headers
and library into src/Makevars, running Rcmd