summ() throws "incorrect number of dimensions" error when using random intercepts lmer model with confint = TRUE

[koenniem]

Description:
When using summ() with an random intercept multilevel model and setting confint = TRUE, the function fails with an index out of bounds error. This is caused by dropped dimensions when computing the confidence intervals.

Reprex:

library(lme4)
#> Loading required package: Matrix
library(jtools)

model <- lmer(Petal.Length ~ 1 + (1 | Species), data = iris)
summ(model, confint = TRUE)
#> Error in the_cis[, 1]: incorrect number of dimensions

^{Created on 2025-06-19 with reprex v2.1.1}

Proposed solution:
When computing the_cis in summ.merMod(), consider adding the drop = FALSE argument to the subset:

the_cis <- confint(model, parm = "beta_", method = conf.method[1], level = ci.width)
the_cis <- the_cis[rownames(the_sum$coefficients), , drop = FALSE]

This argument will prevent the_cis to be simplified from a matrix to a vector when there is only one row (i.e. the intercept).