Dear all, I request your help to solve a problem I've encountered in using
'mice' for multiple imputation.
I want to apply a logistic regression model.
I need to extract information on the fit of the model.
Is there any way to calculate a likelihood ratio or the McFadden-pseudoR2
from the results of the logistic model?
I mean, as it is possible to extract pooled averaging and odds ratio...
Thank you in advance,
Antonello
Here an example of logistic regression on imputed data:
library(mice)
imp <- mice(nhanes)
# logistic regression on the imputed data
fit <- glm.mids((hyp==2)~bmi+chl, data=imp, family = binomial)
summary(fit)
summary(pool(fit)) ### pool averaging across all imputed dataset
summary(pool(fit, method = "rubin1987")) ### pool across all
imputed
dataset
### odds ratio
su <- summary(pool(fit, method = "rubin1987"))[,c(1,6,7)]
stime <- data.frame(exp(su))
names(stime) <- c("OR", "95% low", "95% high")
options(scipen=999)
stime
options(scipen=1)
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