Summary of Bayesian Models as HTML Table

Daniel Lüdecke

2023-08-17

## Loading 'brms' package (version 2.19.0). Useful instructions
## can be found by typing help('brms'). A more detailed introduction
## to the package is available through vignette('brms_overview').

## 
## Attaching package: 'brms'

## The following objects are masked from 'package:rstanarm':
## 
##     dirichlet, exponential, get_y, lasso, ngrps

## The following object is masked from 'package:stats':
## 
##     ar

This vignette shows examples for using tab_model() to create HTML tables for mixed models. Basically, tab_model() behaves in a very similar way for mixed models as for other, simple regression models, as shown in this vignette.

# load required packages
library(sjPlot)
library(brms)

# sample models
zinb <- read.csv("http://stats.idre.ucla.edu/stat/data/fish.csv")
set.seed(123)
m1 <- brm(bf(
    count ~ persons + child + camper + (1 | persons),
    zi ~ child + camper + (1 | persons)
  ),
  data = zinb,
  family = zero_inflated_poisson()
)

data(epilepsy)
set.seed(123)
epilepsy$visit <- as.numeric(epilepsy$visit)
epilepsy$Base2 <- sample(epilepsy$Base, nrow(epilepsy), replace = TRUE)
f1 <- bf(Base ~ zAge + count + (1 |ID| patient))
f2 <- bf(Base2 ~ zAge + Trt + (1 |ID| patient))
m2 <- brm(f1 + f2 + set_rescor(FALSE), data = epilepsy)

tab_model(m1)

tab_model(m2)

tab_model(m2, show.ci50 = TRUE)

tab_model(m1, m2)