Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ---- message=FALSE, warning=FALSE--------------------------------------------
library(dplyr)
library(broom)
m0 <- esoph %>%
mutate_if(is.factor, ~factor(., ordered = FALSE)) %>%
glm(cbind(ncases, ncontrols) ~ agegp + tobgp + alcgp, data = ., family = binomial())
# tidy
tidy(m0)
## -----------------------------------------------------------------------------
library(tidycat)
m0 %>%
tidy() %>%
tidy_categorical(m = m0, include_reference = FALSE)
## -----------------------------------------------------------------------------
m0 %>%
tidy(exponentiate = TRUE) %>%
tidy_categorical(m = m0, exponentiate = TRUE, reference_label = "Baseline") %>%
select(-statistic, -p.value)
## ---- fig.width=6, fig.height=4-----------------------------------------------
# store parameter estimates and confidence intervals (except for the intercept)
d0 <- m0 %>%
tidy(conf.int = TRUE) %>%
slice(-1)
d0
library(ggplot2)
library(tidyr)
ggplot(data = d0,
mapping = aes(x = term, y = estimate, ymin = conf.low, ymax = conf.high)) +
coord_flip() +
geom_hline(yintercept = 0, linetype = "dashed") +
geom_pointrange()
## ---- fig.width=6, fig.height=4-----------------------------------------------
d0 <- m0 %>%
tidy(conf.int = TRUE) %>%
tidy_categorical(m = m0, include_reference = FALSE) %>%
slice(-1)
d0 %>%
select(-(3:5))
ggplot(data = d0,
mapping = aes(x = term, y = estimate, ymin = conf.low, ymax = conf.high,
colour = variable)) +
coord_flip() +
geom_hline(yintercept = 0, linetype = "dashed") +
geom_pointrange()
## ---- fig.width=6, fig.height=4-----------------------------------------------
d0 <- m0 %>%
tidy(conf.int = TRUE) %>%
tidy_categorical(m = m0) %>%
slice(-1)
d0 %>%
select(-(3:5))
library(ggforce)
ggplot(data = d0,
mapping = aes(x = level, y = estimate, colour = reference,
ymin = conf.low, ymax = conf.high)) +
facet_col(facets = vars(variable), scales = "free_y", space = "free") +
coord_flip() +
geom_hline(yintercept = 0, linetype = "dashed") +
geom_pointrange()
## ---- fig.width=6, fig.height=4-----------------------------------------------
ggplot(data = d0,
mapping = aes(x = level, y = estimate,
ymin = conf.low, ymax = conf.high,
colour = reference)) +
facet_row(facets = vars(variable), scales = "free_x", space = "free") +
geom_hline(yintercept = 0, linetype = "dashed") +
geom_pointrange() +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
## -----------------------------------------------------------------------------
m1 <- mtcars %>%
mutate(engine = recode_factor(vs, `0` = "straight", `1` = "V-shaped"),
transmission = recode_factor(am, `0` = "automatic", `1` = "manual")) %>%
lm(mpg ~ as.factor(cyl) + wt * hp + wt * transmission + engine * transmission , data = .)
tidy(m1)
## -----------------------------------------------------------------------------
d1 <- m1 %>%
tidy(conf.int = TRUE) %>%
tidy_categorical(m = m1, n_level = TRUE) %>%
slice(-1)
d1 %>%
select(-(2:7))
## ---- fig.width=6, fig.height=6-----------------------------------------------
ggplot(data = d1,
mapping = aes(x = level, y = estimate, colour = reference,
ymin = conf.low, ymax = conf.high)) +
facet_col(facets = "variable", scales = "free_y", space = "free") +
coord_flip() +
geom_hline(yintercept = 0, linetype = "dashed") +
geom_pointrange()
## ---- fig.width=6, fig.height=5-----------------------------------------------
d1 %>%
dplyr::filter(n_level > 0 | !is.na(term)) %>%
ggplot(mapping = aes(x = level, y = estimate, colour = reference,
ymin = conf.low, ymax = conf.high)) +
facet_col(facets = "variable", scales = "free_y", space = "free") +
coord_flip() +
geom_hline(yintercept = 0, linetype = "dashed") +
geom_pointrange()
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