Quickly Create Elegant Regression Results Tables and Plots when Modelling.
finalfit
The finalfit
package provides functions that help you quickly create elegant final results tables and plots when modelling in R. These can easily be exported as Word documents, PDFs, or html files.
Its design follows Hadley Wickham's tidy tool manifesto.
In addition, it provides functions for identifying and handling missing data, together with a number of functions to bootstrap simulate regression model results.
Installation
You can install finalfit
from CRAN:
install.packages("finalfit")
It is recommended that this package is used together with dplyr
which can be installed via:
install.packages("dplyr")
Documentation
The package documentation is maintained independently at finalfit.org.
Examples
See Get started and the All tables vignettes for extensive examples.
Crosstable / table 1
# Crosstable
explanatory = c("age.factor", "sex.factor", "obstruct.factor")
dependent = 'mort_5yr'
colon_s %>%
summary_factorlist(dependent, explanatory,
p=TRUE, add_dependent_label=TRUE) -> t1
knitr::kable(t1, align=c("l", "l", "r", "r", "r"))
Regression table
explanatory = c("age.factor", "sex.factor",
"obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
finalfit(dependent, explanatory, metrics=TRUE) -> t2
knitr::kable(t2[[1]], row.names=FALSE, align=c("l", "l", "r", "r", "r", "r"))
knitr::kable(t2[[2]], row.names=FALSE, col.names="")
When exported to PDF:
Regression plots
explanatory = c("age.factor", "sex.factor",
"obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
or_plot(dependent, explanatory)