https://github.com/ewenharrison/finalfit

Quickly create elegant regression results tables and plots when modelling in R
https://github.com/ewenharrison/finalfit

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Quickly create elegant regression results tables and plots when modelling in R

• Host: GitHub
• URL: https://github.com/ewenharrison/finalfit
• Owner: ewenharrison
• License: other
• Created: 2018-05-14T20:27:18.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2024-07-23T20:01:27.000Z (4 months ago)
• Last Synced: 2024-07-26T00:13:43.768Z (4 months ago)
• Language: HTML
• Homepage: https://finalfit.org/
• Size: 283 MB
• Stars: 263
• Watchers: 11
• Forks: 29
• Open Issues: 4
• Metadata Files:
  • Readme: README.md

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README

        
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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](https://tidyverse.tidyverse.org/articles/manifesto.html).

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:

``` r

install.packages("finalfit")

```

It is recommended that this package is used together with `dplyr` which can be installed via:

``` r

install.packages("dplyr")

```

## Documentation

The package documentation is maintained independently at [finalfit.org](https://finalfit.org/). 

## Examples

See [Get started](https://finalfit.org/articles/finalfit.html) and the [All tables](https://finalfit.org/articles/all_tables_examples.html) vignettes for extensive examples.  

### Crosstable / table 1

``` r

# 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

``` r

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

``` r

explanatory = c("age.factor", "sex.factor", 

  "obstruct.factor", "perfor.factor")

dependent = 'mort_5yr'

colon_s %>%

  or_plot(dependent, explanatory)

```