Learn R Programming
⚠️There's a newer version (1.0.8) of this package.Take me there.

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.

Copy Link

Version

Install

install.packages('finalfit')

Monthly Downloads

3,297

Version

0.8.9

License

MIT + file LICENCE

Issues

7

Pull Requests

0

Stars

270

Forks

28

Maintainer

Ewen Harrison

Last Published

December 18th, 2018

Functions in finalfit (0.8.9)

extract_variable_label

Extract variable labels from dataframe
boot_compare

Compare bootstrapped distributions
ff_glimpse

Descriptive statistics for dataframe
fit2df

Extract model fit results to dataframe (generic): finalfit model extractors
ff_interaction

Make an interaction variable and add to dataframe
boot_predict

Bootstrap simulation for model prediction
ff_metrics

Generate common metrics for regression model results
ff_newdata

Generate newdata for simulations
finalfit-package

finalfit: Quickly create elegant final results tables and plots when modelling.
ff_label

Label a variable
ff_merge

Merge a summary_factorlist() table with any number of model results tables.
finalfit

Final output tables for common regression models
glmuni

Binomial logistic regression univariable models: finalfit model wrapper
ff_plot

Produce a table and plot
glmmixed

Mixed effects binomial logistic regression models: finalfit model wrapper
summary_factorlist

Summarise a set of factors (or continuous variables) by a dependent variable
extract_labels

Extract variable labels and names
extract_fit

Extract model output to dataframe
summary_factorlist0

Summarise a set of factors by a dependent variable
ff_relabel

Relabel variables in a data frame
hr_plot

Produce a hazard ratio table and plot
missing_df

Missing values data frame
metrics_hoslem

Hosmer-Lemeshow goodness of fit test
missing_glimpse

Summary of missing values
missing_pairs

Missing values pairs plot
missing_compare

Compare missing data
ff_formula

Generate formula as character string
%>%

Pipe operator
remove_intercept

Remove intercept from model output
is.survival

Test character describes survival object
missing_pattern

Characterise missing data for finalfit models
plot_title

Label plot title
lmmixed

Mixed effects linear regression models: finalfit model wrapper
summary_factorlist3

Summarise a set of factors by a dependent variable
glmmulti

Binomial logistic regression multivariable models: finalfit model wrapper
or_plot

Produce an odds ratio table and plot
remove_labels

Remove variable labels.
p_tidy

Round p-values but keep trailing zeros
missing_plot

Missing values occurence plot
missing_predictorMatrix

Create predictorMatrix for use with mice
glmmulti_boot

Binomial logistic regression multivariable models with bootstrapped confidence intervals: finalfit model wrapper
surv_plot

Plot survival curves with number-at-risk table
variable_type

Determine type/class of a variable
lmmulti

Linear regression multivariable models: finalfit model wrapper
summary_factorlist4

Summarise a set of factors by a dependent variable
lmuni

Linear regression univariable models: finalfit model wrapper
round_tidy

Round values but keep trailing zeros
rm_duplicate_labels

Remove duplicate levels within summary_factorlist: finalfit helper function
summary_formula

Call to Hmisc:::summary.formula
summary_factorlist5

Summarise a set of factors by a dependent variable
summary_factorlist1

Summarise a set of factors by a dependent variable
summary_factorlist2

Summarise a set of factors by a dependent variable
coefficient_plot

Produce a coefficient table and plot
colon_s

Chemotherapy for Stage B/C colon cancer
coxphmulti

Cox proprotional hazards multivariable models: finalfit model wrapper
coxphuni

Cox proprotional hazards univariable models: finalfit model wrapper
%<>%

magrittr compound assignment pipe-operator
condense_fit

Condense model output dataframe for final tables
dependent_label

Make a label for the dependent variable
error_colon_fct_levels

Errors: colon in factor levels