View source: R/display-logistic.R
display_logistic | R Documentation |
Given a fit
object, univariable and (optionally) multivariable results from
logistic regression are displayed in a format suitable for presentation.
display_logistic(
fit,
data,
add_multi = FALSE,
format = "html",
conf_level = 0.95,
exponentiate = TRUE,
include_last_row = TRUE
)
fit |
An object of class |
data |
A tibble or data frame with the full data set. |
add_multi |
Logical; include multivariable results. Default is |
format |
Display format in case I need to escape some characters. A place holder for now in case I need it in the future. Default is "html". |
conf_level |
The confidence level to use for the confidence interval. Must be strictly greater than 0 and less than 1. Defaults to 0.95, which corresponds to a 95 percent confidence interval. |
exponentiate |
Logical indicating whether or not to exponentiate the
the coefficient estimates. This is typical for logistic and multinomial
regressions, but a bad idea if there is no log or logit link. Defaults to
|
include_last_row |
Adds a row at the end of each set of results to give
some breathing room. Default is |
A tibble
## Not run:
library(epiDisplay)
library(tidyverse)
dplyr::glimpse(infert)
model0 <- glm(case ~ induced + spontaneous + education,
family = binomial,
data = infert)
summary(model0)
display_logistic(fit = model0,
data = infert)
display_logistic(fit = model0,
data = infert,
add_multi = TRUE)
# How does an interaction term work?
# This sort of works right now, but still needs work (2019-03-23)
model0 <- glm(case ~ induced * education,
family = binomial,
data = infert)
summary(model0)
display_logistic(fit = model0,
data = infert,
add_multi = FALSE)
display_logistic(fit = model0,
data = infert,
add_multi = TRUE)
#### Another data set --------------------------------
library(compareGroups)
data(predimed)
dplyr::glimpse(predimed)
predimed <- predimed %>%
mutate_if(is.double, as.double)
fit = glm(htn ~ sex + bmi + smoke,
family = binomial(link = "logit"),
data = predimed)
display_logistic(fit = fit,
data = predimed,
add_multi = TRUE)
## End(Not run)
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