**September 17th**, and is expected to return by the end of the day on Wednesday, **September 18th**. During this period, the backend will be updated and the website will get a refreshed look.

Would you like to financially support the OpenMx Project? Go to www.support.vcu.edu, enter a dollar amount into the text box, and click the "CONTINUE" button. On the new page, click the "SEARCH" button, select "All" from the drop-down list, and type "OpenMx" into the search box. Then, click the "NEXT" button to finalize and submit your donation. Donations may be made by credit/debit card or by using the account number of a checking account.

**OpenMx** is free and open source software for use with **R** that allows estimation of a wide variety of advanced multivariate statistical models. **OpenMx** consists of a library of functions and optimizers that allow you to quickly and flexibly define an SEM model and estimate parameters given observed data.

**OpenMx** runs on MacOS, Windows, and most varieties of Linux/GNU. This means the same scripts you write in Windows will run in MacOS or Linux.

**OpenMx** can be used by those who think in terms of path models or by those who prefer to specify models in terms of matrix algebra. **OpenMx** is extremely powerful, taking full advantage of the **R** programming environment. This means that complicated models and data sets can be specified and modified using the **R** language. In order to give a very brief idea of what **OpenMx** looks like, here are two small demo examples: one from a path modeler's perspective and one from a matrix algebra perspective.

Here is a path diagram for a one factor path model with five indicators. Beside it is an R script using **OpenMx** path modeling commands to read the data from disk, create the one factor model, fit the model to the observed covariances, and print a summary of the results.

require(OpenMx) data(demoOneFactor) manifests <- names(demoOneFactor) latents <- c("G") factorModel <- mxModel("One Factor", type="RAM", manifestVars = manifests, latentVars = latents, mxPath(from=latents, to=manifests,values=0.8), mxPath(from=manifests, arrows=2,values=1), mxPath(from=latents, arrows=2, free=FALSE, values=1.0), mxData(cov(demoOneFactor), type="cov", numObs=500)) summary(factorModelFit <- mxRun(factorModel)) |

For more information, see our Youtube playlist on path-specified modeling.

**OpenMx** can also specify models in terms of matrix algebra. On the left is an equation for the same one factor path model with five indicators. Beside it is an R script using **OpenMx** matrix modeling commands to read the data from disk, create the one factor model, fit the model to the observed covariances, and print a summary of the results.

require(OpenMx) data(demoOneFactor) factorModel <- mxModel("One Factor", mxMatrix("Full", 5, 1, values=0.8, free=TRUE, name="A"), mxMatrix("Symm", 1, 1, values=1, free=FALSE, name="L"), mxMatrix("Diag", 5, 5, values=1, free=TRUE, name="U"), mxAlgebra(A %*% L %*% t(A) + U, name="R"), mxExpectationNormal(covariance = "R", dimnames = names(demoOneFactor)), mxFitFunctionML(), mxData(cov(demoOneFactor), type="cov", numObs=500)) summary(factorModelFit <- mxRun(factorModel)) |

For more information, see our Youtube playlist on matrix-specified modeling.

This site is a community project to develop **OpenMx** software and the models and scripts that allow researchers to perform their analyses as quickly and easily as possible. Originally, **OpenMx** was funded by a grant from the **National Institutes of Health Roadmap** and was located in the **Human Dynamics Lab** in the **Department of Psychology** at the **University of Virginia**. Our current efforts are partially funded by a grant from the **National Institute on Drug Abuse (NIDA)**. The project is developed in a multisite collaboration between University of Virginia, Georgia Tech, Virginia Commonwealth University, Pennsylvania State University, and University of Edinburgh. The **OpenMx** team provides a binary download of OpenMx software, source code for OpenMx, documentation for OpenMx, the OpenSEM Community Wiki, and the OpenSEM Discussion Forums for users of all types of software to discuss issues in multivariate statistical modeling and to work together to create open source scripts that we can all use to advance inquiry in a wide variety of biological, medical, epidemiological, genetic, and behavioral sciences.