On Nov 7, 2010, at 1:24 PM, Robin Jeffries wrote:
What does missInfo compute
help(package=mitools)
And some obvious Goggling ("lumley micombine missinfo") produced this
link to a 2005 course syllabus that Lumley (the package author) leaves
online:
http://courses.washington.edu/b570/lectures.html
and how is it computed?
> methods(MIcombine)
[1] MIcombine.default*
getAnywhere(MIcombine.default)
--
David.
There is only 1 observation missing the ethnic3 variable. There is
no other
missing data.
N=1409
summary(MIcombine(mod1))
Multiple imputation results:
with(rt.imp, glm(G1 ~ stdage + female + as.factor(ethnic3) + u,
family = binomial()))
MIcombine.default(mod1)
results se
(lower upper) missInfo
(Intercept) -0.40895453 0.14743928 -0.70805544
-0.1098536
53 %
stdage 0.13991360 0.06046537 0.02140364
0.2584236 0 %
female -0.05587635 0.11083362 -0.27310639
0.1613537 0 %
as.factor(ethnic3)1 0.17297835 0.19556664 -0.21032531
0.5562820 0
%
as.factor(ethnic3)2 0.63507020 0.18017975 0.28192410
0.9882163 0
%
u -0.01322976 0.18896230 -0.40291914
0.3764596 64 %
Thanks,
Robin Jeffries
MS, DrPH Candidate
Department of Biostatistics
UCLA
530-624-0428
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