README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
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)
```

# forestmodel

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This is an R package to generate forest plots of the coefficients of models produced
by `lm`, `glm`, `survival::coxph`, etc.

The main function is `forest_model`, with a helper function `default_forest_panels` to produce
the necessary `panels` `data.frame`.

## Installation

The package can be installed using `install.packages`. It needs Hadley Wickham's
`broom`, `dplyr`, `gpplot2` and `lazyeval` packages.

Development takes place on the github repository https://github.com/NikNakk/forestmodel/.

## Installation

You can install the released version of forestmodel from [CRAN](https://CRAN.R-project.org) with:

``` r
install.packages("forestmodel")
```

And the development version from [GitHub](https://github.com/) with:

``` r
# install.packages("devtools")
devtools::install_github("NikNakk/forestmodel")
```
## Example

```{r example, message = FALSE}
library(forestmodel)
library(survival)
library(dplyr)
pretty_lung <- lung %>%
  transmute(time,
            status,
            Age = age,
            Sex = factor(sex, labels = c("Male", "Female")),
            ECOG = factor(lung$ph.ecog),
            `Meal Cal` = meal.cal)

print(forest_model(coxph(Surv(time, status) ~ ., pretty_lung)))
```

Specifying the covariates to show:

```{r, select_variables}
print(forest_model(coxph(Surv(time, status) ~ ., pretty_lung), 
                   covariates = c("Age", "Sex")))
```