# pgee.mixed

Penalized Generalized Estimating Equations for Bivariate Mixed
Outcomes

Perform simultaneous estimation and variable selection for correlated
bivariate mixed outcomes (one continuous outcome and one binary outcome
per cluster) using penalized generalized estimating equations. In
addition, clustered Gaussian and binary outcomes can also be modeled.
The SCAD, MCP, and LASSO penalties are supported. Cross-validation can
be performed to find the optimal regularization parameter(s).

## Installation from GitHub:

```
if (!require("devtools"))
install.packages("devtools")
devtools::install_github("kaos42/pgee.mixed")
```

### Installation note for OS X
users:

This package uses Rcpp and RcppArmadillo. Mac OS X users may see the
following error in their console while trying to install the
package:

```
ld: warning: directory not found for option '-L/usr/local/lib/gcc/x86_64-apple-darwin13.0.0/4.8.2'
ld: library not found for -lgfortran
```

The solution is documented here.
In a nutshell, type the following in a terminal:

```
curl -O http://r.research.att.com/libs/gfortran-4.8.2-darwin13.tar.bz2
sudo tar fvxz gfortran-4.8.2-darwin13.tar.bz2 -C /
```

## To do list

If there is sufficient interest in this package, the following
features could be added:

- Families other than Gaussian and binomial.

- Working correlation structures other than independence, compound
symmetry, and AR(1).

- Specify a vector of cluster ids rather than force the equal cluster
size structure.

- Users can provide fixed working correlation and dispersion
parameters.

- Users can provide an index vector specifying which parameters are
not to be penalized.

- Add a ridge component to existing penalties.