This is a page of example models. To learn about installing click here, for the OpenMx documentation and learning about path-based model and matrix syntax click here. *note*: It is a new page for April 2019: If we go with this wiki as the basis for collecting all OpenMx Scripts, links will be added here.
Basic Supported Methods
Confirmatory Factor Analysis
- One Factor Models
- Multiple Factor Models
- Ordinal Factor Analysis
- Joint Ordinal/Continuous Factor Analysis
SEM, Indirect Effects, and Mediation
- Regression
- Ordinal Regression
- Mediation and Why Not to Use It
Measurement Models and Psychometrics
- Item Response Theory
- Item Factor Analysis
- Measurement Invariance
- Differential Item Functioning
- Test Equating
Multiple Groups
- Raw Data
- Weighted Least Squares
- Extracting Means, Covariances, and Thresholds with mxGetExpected
Growth and Change
- Latent Growth Model in Path Form, Matrix Form, and in Not One but Two Other Styles
- Latent Growth Mixture Model in Path Form and Matrix Form
- Regime Switching Model
- Independent Mixture Model with mxExpectationMixture
- Growth Mixture Model
- Factor Mixture Model
- Dynamical Systems Analysis
- Latent Differential Equations
Multilevel SEM
- Multilevel SEM
- Multilevel Regression Models
- Multilevel Factor Models
- Multilevel Structural Equation Models
- Multilevel Mediation Models
- Moderation
- Mediated Moderation Models
- Product of Latent Variables
Latent Classes
- Latent Class Analysis
- Latent Profile Analysis
- Latent Transition Analysis
- Latent Factor Regression
- State Space Models
- Single-Subject Models
- Multi-Subject Models
- Hidden Markov Models
- Network Models
Modeling Different Types of Data Correctly
- Continuous Variables
- Ordinal Variables
- Joint Ordinal & Continuous Variables
- Contingency Tables
- Gaussian Copulas
- Polychoric/Polyserial Correlations
Modeling Predictors, Effects, Definition Variables, Weights, Missingness Correctly
- Exogenous Predictors
- Definition Variables
- Fixed & Random Effects
- Sample Weights
- Missing Data
- Missing at Random
- Non-Ignorable Missingness
- Censoring
How Do I Simulate Data, Power...
- Simulations
- Power Analysis with mxPower and mxPowerSearch
- Meta Analysis with metaSEM
- Multiple Group Analysis
Twin Models
- umx includes many twin models including ACE, ACEv, simplex, sex-limitation, GxE, common pathway, independent pathway, etc.
- Genetic Epidemiology: Numerous examples from Hermine Maes
- ACE / ADE
- Univariate / Multivariate
- Sex Limitation
- GxE Interaction
- Direction of Causation
- Two-Stage Twin Family Models
- Assortative Mating Models
- Extended Pedigree Models
- Niche Selection
GREML and Genomic SEM
- GREML and Genomic SEM
- Molecular Genetic Variance Component Analysis (GREML, GCTA)
- Genomic Relatedness Matrix
- Restricted Maximum Likelihood
- Genetic Association Analysis
Optimizers
- Full Information Maximum Likelihood
- Restricted Maximum Likelihood
- Weighted Least Squares
- Gradient-Based Quasi-Newton
- Newton-Raphson
- Direct Search - Nelder Mead
- Stochastic Global Optimization
- Expectation-Maximization (EM)
- User Defined Fit Functions
- Custom Compute Plans
Parameter Estimates and Fit Statistics
- Goodness-of-Fit
- Getting Chi-Squared Statistics with mxRefModels
- Using mxSE to Get Standard Errors of Functions of Free Parameters
- Using mxCI for Profile Likelihood Confidence Intervals
- Using mxMI for Model Modification Bootstrapping
- Robust Standard Errors
- Factor Scores
- Jack-Knifing
- Cross-Validation
- Modification Indices with mxMI
- Bootstrap Likelihood Ratio Tests
How Do I Add Covariates, Different Intervals for Growth...
- Fixed Ages for All Participants
- Variable Ages or Assessment Intervals for All Participants
- Data Harmonization
How To
- How Do I Plot Results?
- How to Pick Starting Values
- Leave Them at Zero
- Make an Educated Guess
- Use mxAutoStart
- Error Status Codes
Misc
- Cloud & Big Data
- Brownie Baking
- Donating Money
- Retro Mx