Aliases: smi
Keywords: datasets
### ** Examples data(smi) with(smi, table(sex, drkfre))
[[1]] drkfre sex Non drinker not in last wk <3 days last wk >=3 days last wk 0 282 201 105 12 1 207 194 134 35 [[2]] drkfre sex Non drinker not in last wk <3 days last wk >=3 days last wk 0 282 195 109 14 1 200 200 132 38 [[3]] drkfre sex Non drinker not in last wk <3 days last wk >=3 days last wk 0 278 202 109 11 1 209 194 131 36 [[4]] drkfre sex Non drinker not in last wk <3 days last wk >=3 days last wk 0 284 188 114 14 1 203 206 128 33 [[5]] drkfre sex Non drinker not in last wk <3 days last wk >=3 days last wk 0 288 191 109 12 1 206 192 136 36 attr(,"call") with(smi, table(sex, drkfre))
model1<-with(smi, glm(drinkreg~wave*sex, family=binomial())) MIcombine(model1)
Multiple imputation results:
with(smi, glm(drinkreg ~ wave * sex, family = binomial()))
MIcombine.default(model1)
results se
(Intercept) -2.25974358 0.26830731
wave 0.24055250 0.06587423
sex 0.64905222 0.34919264
wave:sex -0.03725422 0.08609199
summary(MIcombine(model1))
Multiple imputation results:
with(smi, glm(drinkreg ~ wave * sex, family = binomial()))
MIcombine.default(model1)
results se (lower upper) missInfo
(Intercept) -2.25974358 0.26830731 -2.78584855 -1.7336386 4 %
wave 0.24055250 0.06587423 0.11092461 0.3701804 12 %
sex 0.64905222 0.34919264 -0.03537187 1.3334763 1 %
wave:sex -0.03725422 0.08609199 -0.20623121 0.1317228 7 %