`rmda`

: Risk Model
Decision AnalysisThe package `rmda`

(risk model decision analysis) provides
tools to evaluate the value of using a risk prediction instrument to
decide treatment or intervention (versus no treatment or intervention).
Given one or more risk prediction instruments (risk models) that
estimate the probability of a binary outcome, `rmda`

provides
functions to estimate and display decision curves and other figures that
help assess the population impact of using a risk model for clinical
decision making. Here, “population” refers to the relevant patient
population.

Decision curves display estimates of the (standardized) net benefit
over a range of probability thresholds used to categorize observations
as ‘high risk.’ The curves help evaluate a treatment policy that
recommends treatment for patients who are estimated to be ‘high risk’ by
comparing the population impact of a risk-based policy to “treat all”
and “treat none” intervention policies. Curves can be estimated using
data from a prospective cohort. In addition, `rmda`

can
estimate decision curves using data from a case-control study if an
estimate of the population outcome prevalence is available. Version 1.5
of the package provides an alternative framing of the decision problem
for situations where treatment is the standard-of-care and a risk model
might be used to recommend that low-risk patients (i.e., patients below
some risk threshold) opt out of treatment.

Confidence intervals calculated using the bootstrap can be computed and displayed. A wrapper function to calculate cross-validated curves using k-fold cross-validation is also provided.

Key functions are:

`decision_curve`

: Estimate (standardized) net benefit curves with bootstrap confidence intervals.`plot_decision_curve`

: Plot a decision curve or multiple curves.`plot_clinical_impact`

and`plot_roc_components`

: Alternative plots for the output of`decision_curve`

showing measures of clinical impact or the components of the ROC curve (true/false positive rates) across a range of risk thresholds. See help files or tutorial for more info.`cv_decision_curve`

: Calculate k-fold cross-validated estimates of a decision curve and its components.

The easiest way to get the package is directly from CRAN:

`install.packages("rmda")`

or install the package directly from github using devtools.

```
## install.packages("devtools")
library(devtools)
install_github("mdbrown/rmda")
```

You may also download the current version of the package here:

https://github.com/mdbrown/rmda/releases

navigate to the source package and use

```
install.packages("../rmda_1.5.tar.gz",
repos = NULL,
type = "source")
```

Click here for a tutorial to get you started.