What does missInfo compute and how is it computed?
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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