`show_ranef()`

allows a user estimating a mixed model to quickly
plot the random intercepts (with conditional variances) of a given random effect
in a mixed model. In cases where there is a random slope over the intercept, the function
plots the random slope as another caterpillar plot (as another facet)

show_ranef(data, grp, reorder = TRUE)

data | a fitted mixed model with random intercepts |
---|---|

grp | What random intercept/slopes do you want to see as a caterpillar plot? Declare it as a character |

reorder | optional argument. DEFAULT is TRUE, which ``re-orders'' the intercepts by the original value in the data. If FALSE, the ensuing caterpillar plot defaults to a default method of ordering the levels of the random effect by their estimated conditional mode. |

`show_ranef()`

returns a caterpillar plot of the random intercepts from a given
mixed model. If `broom.mixed::augment()`

can process it, this function should work just fine.

This function is a simple wrapper in which `broom.mixed`

and, obviously
`ggplot2`

are doing the heavy lifting.

Steven V. Miller

library(lme4) library(stevemisc) data(sleepstudy) M1 <- lmer(Reaction ~ Days + (Days | Subject), data=sleepstudy) show_ranef(M1, "Subject")show_ranef(M1, "Subject", reorder=FALSE)