README.Rmd

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output: github_document
---

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```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# Cureit

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This package allows you to easily fit and report results from cure mixture models using a tidy framework. The package includes functions to:

- Fit mixture cure models 
- Summarize coefficients using tidiers and gtsummary
- Vizualize the data using nomograms
- Assess model results with Brier scores and K-indicies

## Installation

You can install {cureit} with the following code:

```{r ,eval=F}
remotes::install_github("karissawhiting/cureit")
```

Load the package:

```{r}
library(cureit)
```

# Fit Mixture Cure Models

Functions to fit the models are wrappers for the `smcure()` function from the {smcure} package with the additional capability of passing a formula and directly passing categortical variables without first creating a model matrix:

```{r}
p <- cureit(surv_formula = Surv(ttdeath, death) ~ age,
   cure_formula = ~ age,
   data = trial)

p$surv_coefs

p$cure_coefs
```


# Contributing

Please note that the cureit project is released with a [Contributor Code
of Conduct](http://www.karissawhiting.com/cureit/CODE_OF_CONDUCT.html).
By contributing to this project, you agree to abide by its terms.

Thank you to [Sabrina Lin (@stl2137)](https://github.com/stl2137) for package contributions!