Mx is a combination of a matrix algebra interpreter and a numerical optimizer. It enables exploration of matrix algebra through a variety of operations and functions. There are many built-in fit fuctions to enable structural equation modeling and other types of statistical modeling of data. It offers the fitting fuctions found in commercial software such as LISREL, LISCOMP, EQS and CALIS, along with facilities for maximum likelihood estimation of parameters from missing data structures, under normal theory. Complex ’nonstandard’ models are easy to specify. For further general applicability, it allows the user to define their own fit functions, and optimization may be performed subject to linear and nonlinear equality or boundary constraints.

References in zbMATH (referenced in 14 articles )

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  1. Neale, Michael C.; Hunter, Michael D.; Pritikin, Joshua N.; Zahery, Mahsa; Brick, Timothy R.; Kirkpatrick, Robert M.; Estabrook, Ryne; Bates, Timothy C.; Maes, Hermine H.; Boker, Steven M.: OpenMX 2.0: extended structural equation and statistical modeling (2016)
  2. Pek, Jolynn; Wu, Hao: Profile likelihood-based confidence intervals and regions for structural equation models (2015)
  3. Guo, Xiaobo; Jin, Tian; Wang, Xueqin; Zhang, Heping; Zhong, Shouqiang: Statistical inference of biometrical genetic model with cultural transmission (2013)
  4. Tsai, Miao-Yu: Assessing inter- and intra-agreement for dependent binary data: a Bayesian hierarchical correlation approach (2012)
  5. Tsou, Chi-Ming: On the exploration of linear latent effect for multivariate modeling (2012)
  6. Yves Rosseel: lavaan: An R Package for Structural Equation Modeling (2012) not zbMATH
  7. Boker, Steven; Neale, Michael; Maes, Hermine; Wilde, Michael; Spiegel, Michael; Brick, Timothy; Spies, Jeffrey; Estabrook, Ryne; Kenny, Sarah; Bates, Timothy; Mehta, Paras; Fox, John: OpenMx: an open source extended structural equation modeling framework (2011)
  8. Lu, Tong-Yu; Poon, Wai-Yin; Tsang, Yim-Fan: Latent growth curve modeling for longitudinal ordinal responses with applications (2011)
  9. von Oertzen, Timo; Boker, Steven M.: Time delay embedding increases estimation precision of models of intraindividual variability (2010)
  10. Gjessing, Håkon K.; Lie, Rolv Terje: Biometrical modelling in genetics: are complex traits too complex? (2008)
  11. Lee, Sik-Yum (ed.): Handbook of latent variable and related models. (2007)
  12. Tang, Man-Lai; Poon, Wai-Yin: Statistical inference for equivalence trials with ordinal responses: a latent normal distribution approach (2007)
  13. Olinsky, Alan; Chen, Shaw; Harlow, Lisa: The comparative efficacy of imputation methods for missing data in structural equation modeling. (2003)
  14. Oud, Johan H. L.; Jansen, Robert A. R. G.: Continuous time state space modeling of panel data by means of sem (2000)