README.Rmd

---
  output:
    md_document:
      variant: markdown_github
---

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

  ```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
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  fig.path = "README-"
)
options(width = 60, digits = 3)
```

# dsMice

## Multivariate Imputation by Chained Equations for DataSHIELD - Server

The [`mice`](https://github.com/stefvanbuuren/mice) package
creates multiple imputations (replacement values) for multivariate
missing data.

The [`DataSHIELD`](https://github.com/datashield) framework is a
platform for federated data analysis that brings the algorithm to
the data.

The [`dsMiceClient`](https://github.com/stefvanbuuren/dsMiceClient) package is an
add-on to `mice` that makes multiple imputation available for federated data systems.
This is the package that the `DataSHIELD` end user installs locally.

The [`dsMice`](https://github.com/stefvanbuuren/dsMice) package is part of the
`DataSHIELD` infrastructure. This is the package that the `DataSHIELD` node
owner installs on the server.

## Installation

The following code installs the `dsMice` package on the node server:

  ```{r eval = FALSE}
devtools::install_github("stefvanbuuren/dsMice")
```

In order to work well, the end user should that the 
[`dsMiceClient`](https://github.com/stefvanbuuren/dsMiceClient) package
installed locally.

## Note

Warning: This is an experimental feature. These function do not yet actually work. If you have ideas about the integration of `mice` and `DataSHIELD` feel free to join in.

## Related initiative

Related work appears in [`gflcampos/dsMice`](https://github.com/gflcampos/dsMice) and
[`gflcampos/dsMiceClient`](https://github.com/gflcampos/dsMiceClient).

## Minimal example

Include minimal example here using public DataSHIELD nodes.