OpenMx 2.0 is a new software package for structural equation and other statistical modeling. It introduces a modular approach that separates model expectations from fit functions and optimizers. Major improvements include swappable open-source optimizers like CSOLNP, new methodologies such as Item Factor Analysis and State-space modeling, and new model expectation functions. The software also includes helper functions for standardizing parameters and computing Jacobian-based standard errors, and improved tab completion in the R Graphical User Interface. OpenMx 2.0 allows users to specify models in various ways, including path notation, RAM, LISREL, or arbitrary matrix algebras. It supports multiple fit functions and optimizers, including CSOLNP and NLopt. The software is open-source, modular, and accessible, enabling users to extend and modify it. OpenMx 2.0 also supports parallel computation via Symmetric Multiprocessing (SMP) on multicore systems. The software includes new expectation functions such as mxExpectationRAM, mxExpectationNormal, mxExpectationLISREL, and mxExpectationStateSpace. These functions allow for greater flexibility in specifying model expectations and fit functions. OpenMx 2.0 also supports binary and ordinal data, with threshold matrices for handling such data. The software includes new fit functions such as mxFitFunctionML, mxFitFunctionAlgebra, mxFitFunctionMultigroup, and mxFitFunctionRow. These functions allow for a variety of fitting methods, including maximum likelihood, algebraic optimization, multi-group modeling, and row-wise fitting. OpenMx 2.0 also includes new features such as Item Factor Analysis (IFA), which is well-suited for Item Response Theory models. The software also includes improved output and reporting, including support for saturated and independence models, and standardized parameter estimates. OpenMx 2.0 is a full-featured, open-source xSEM package that runs on most operating systems and supports a wide range of models and modern computing architectures. It is designed to be both open-source and modular, allowing for transparency and extensions to handle new models and paradigms. OpenMx can exist not just as a stand-alone xSEM package, but as a vehicle by which SEM can be learned and integrated into other statistical methods.OpenMx 2.0 is a new software package for structural equation and other statistical modeling. It introduces a modular approach that separates model expectations from fit functions and optimizers. Major improvements include swappable open-source optimizers like CSOLNP, new methodologies such as Item Factor Analysis and State-space modeling, and new model expectation functions. The software also includes helper functions for standardizing parameters and computing Jacobian-based standard errors, and improved tab completion in the R Graphical User Interface. OpenMx 2.0 allows users to specify models in various ways, including path notation, RAM, LISREL, or arbitrary matrix algebras. It supports multiple fit functions and optimizers, including CSOLNP and NLopt. The software is open-source, modular, and accessible, enabling users to extend and modify it. OpenMx 2.0 also supports parallel computation via Symmetric Multiprocessing (SMP) on multicore systems. The software includes new expectation functions such as mxExpectationRAM, mxExpectationNormal, mxExpectationLISREL, and mxExpectationStateSpace. These functions allow for greater flexibility in specifying model expectations and fit functions. OpenMx 2.0 also supports binary and ordinal data, with threshold matrices for handling such data. The software includes new fit functions such as mxFitFunctionML, mxFitFunctionAlgebra, mxFitFunctionMultigroup, and mxFitFunctionRow. These functions allow for a variety of fitting methods, including maximum likelihood, algebraic optimization, multi-group modeling, and row-wise fitting. OpenMx 2.0 also includes new features such as Item Factor Analysis (IFA), which is well-suited for Item Response Theory models. The software also includes improved output and reporting, including support for saturated and independence models, and standardized parameter estimates. OpenMx 2.0 is a full-featured, open-source xSEM package that runs on most operating systems and supports a wide range of models and modern computing architectures. It is designed to be both open-source and modular, allowing for transparency and extensions to handle new models and paradigms. OpenMx can exist not just as a stand-alone xSEM package, but as a vehicle by which SEM can be learned and integrated into other statistical methods.