Nothing
## ----echo = FALSE-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>", dev = "png", fig.width = 7, fig.height = 5, message = FALSE, warning = FALSE)
if (!requireNamespace("sjlabelled", quietly = TRUE) ||
!requireNamespace("sjmisc", quietly = TRUE) ||
!requireNamespace("haven", quietly = TRUE) ||
!requireNamespace("ggplot2", quietly = TRUE)) {
knitr::opts_chunk$set(eval = FALSE)
} else {
knitr::opts_chunk$set(eval = TRUE)
library(sjPlot)
}
## ----results='hide'-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
library(sjPlot)
library(sjlabelled)
library(sjmisc)
library(ggplot2)
data(efc)
theme_set(theme_sjplot())
## ----results='hide'-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
# create binary response
y <- ifelse(efc$neg_c_7 < median(na.omit(efc$neg_c_7)), 0, 1)
# create data frame for fitting model
df <- data.frame(
y = to_factor(y),
sex = to_factor(efc$c161sex),
dep = to_factor(efc$e42dep),
barthel = efc$barthtot,
education = to_factor(efc$c172code)
)
# set variable label for response
set_label(df$y) <- "High Negative Impact"
# fit model
m1 <- glm(y ~., data = df, family = binomial(link = "logit"))
## -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
plot_model(m1)
## -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
plot_model(m1, vline.color = "red")
## -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
plot_model(m1, sort.est = TRUE)
## -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
summary(m1)
## -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
plot_model(m1, order.terms = c(6, 7, 1, 2, 3, 4, 5))
## -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
plot_model(m1, transform = NULL)
plot_model(m1, transform = "plogis")
## -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
plot_model(m1, show.values = TRUE, value.offset = .3)
## -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
data(iris)
m2 <- lm(Sepal.Length ~ Sepal.Width + Petal.Length + Species, data = iris)
# variable names as labels, but made "human readable"
# separating dots are removed
plot_model(m2)
# to use variable names even for labelled data
plot_model(m1, axis.labels = "", title = "my own title")
## -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
# keep only coefficients sex2, dep2 and dep3
plot_model(m1, terms = c("sex2", "dep2", "dep3"))
# remove coefficients sex2, dep2 and dep3
plot_model(m1, rm.terms = c("sex2", "dep2", "dep3"))
## -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
plot_model(m2, type = "std")
## ----results='hide'-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
if (require("rstanarm", quietly = TRUE)) {
# make sure we apply a nice theme
library(ggplot2)
theme_set(theme_sjplot())
data(mtcars)
m <- stan_glm(mpg ~ wt + am + cyl + gear, data = mtcars, chains = 1)
# default model
plot_model(m)
# same model, with mean point estimate, dot-style for point estimate
# and different inner/outer probabilities of the HDI
plot_model(
m,
bpe = "mean",
bpe.style = "dot",
prob.inner = .4,
prob.outer = .8
)
}
## -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
plot_model(
m1,
colors = "Accent",
show.values = TRUE,
value.offset = .4,
value.size = 4,
dot.size = 3,
line.size = 1.5,
vline.color = "blue",
width = 1.5
)
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.