Extract the number of groups of a model when using modelsummary

Question

I am using the modelsummary package to create a table for a multilevel logistic regression model estimated via glmer from the lme4 package. I would know like to include the number of groups in my table. The information does not appear in get_gof(model), but it exists if I type in summary(model). In the example below, I would like to have one row with the information: Number of groups: 18.

A minimum reproducible example:

# Load the required packages
library(lme4)

# Load the sleepstudy dataset
data(sleepstudy)

# Convert the dependent variable to a binary outcome
sleepstudy$binary_outcome <- ifelse(sleepstudy$Reaction > median(sleepstudy$Reaction), 1, 0)

# Run the multilevel logistic regression model using glmer
model <- glmer(binary_outcome ~ Days + (1 | Subject), data = sleepstudy, family = binomial())

# Print the model summary
summary(model)

# Use Modelsummary to print the table
modelsummary(models, 
             output = "table.docx", 
             coef_map = cm, title = 'Table 1', 
             exponentiate = TRUE,
             stars = T)

Answer 1

You can use the glance_custom mechanism to add any custom goodness-of-fit statistic to a table. I paste a solution to your question below. You can find detailed explanations and many more examples on the modelsummary website:

https://vincentarelbundock.github.io/modelsummary/articles/modelsummary.html#new-models-and-custom-statistics

library(lme4)
library(tibble)
library(modelsummary)
data(sleepstudy)
sleepstudy$binary_outcome <- ifelse(sleepstudy$Reaction > median(sleepstudy$Reaction), 1, 0)
model <- glmer(binary_outcome ~ Days + (1 | Subject), data = sleepstudy, family = binomial())

glance_custom.glmerMod <- function(x, ...) {
  tibble(`# Groups` = summary(x)$ngrps)
}

modelsummary(model)

	(1)
(Intercept)	-3.460
	(0.937)
Days	0.743
	(0.130)
SD (Intercept Subject)	2.820
Num.Obs.	180
R2 Marg.	0.289
R2 Cond.	0.792
AIC	158.6
BIC	168.2
ICC	0.7
RMSE	0.28
# Groups	18