Nagelkerke r-square in multiple imputed datasets

[AngeloArias97]

Dear Prof. van Buuren,

Thank you for developing such an amazing tool. I was wondering if you can guide me to obtain Nagelkerke r-square value from my logistic regression model.

See an example of my code.

model1 <- with(imp, {
data <- data.frame(
lapply(seq_along(exposome_factors), function(i) {
as.numeric(get(exposome_factors[i])) * coefficients[i]
})
)
colnames(data) <- exposome_factors
data$ES_SCZ <- rowSums(data) + 2
data$ES_SCZ <- scale(data$ES_SCZ)
data$ES_SCZ <- ifelse(data$ES_SCZ >= quantile(data$ES_SCZ, 0.75, na.rm = TRUE), 1, 0)
glm(PE_18_Distressing ~ ES_SCZ + sex + maternal_education + imd_income_1993_maternal, data = data, family = binomial)
})

pooled_results1 <- pool(model1)
summary(pooled_results1, conf.int = TRUE)

In stackoverflow i found this answer, do you think is appropriate for my case? https://stackoverflow.com/questions/65245547/using-mice-inputed-data-sets-in-glm-analysis-can-pooled-model-fit-indices-be-ob

Thank you so much!