Everything OpenMx can do, with commented examples, how-to guides, and tutorials

Everything OpenMx can do, with commented examples.md

This is a page of example models. To learn about installing click here, to learn about path-based model syntax click here.

Three basic methods of modeling supported in OpenMx

• Path analysis
• RAM - LISREL
• Matrix algebra

Confirmatory Factor Analysis

• One factor models
• Multiple factor models
• Ordinal factor analysis
• Joint ordinal/continuous factor analysis

SEM (including indirect effects and mediation analysis)

• Regression with structural equation models
• Ordinal regression
• Mediation and why not to use it: Hunter

Measurement models and Psychometrics

• Item response theory
• Item factor analysis
• Measurement invariance
• Differential item functioning
• Test equating

Multiple groups

Growth and change

• Latent growth models
• Latent growth mixture models
• Regime switching models
• Independent mixture models
• Mixture structural equation models
• Factor mixture models
• Dynamical systems analysis
• Latent differential equations

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
• Meta analysis
• Multiple group analysis

Twin Models

• 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

• Molecular genetic variance component analysis
• Genomic Relatedness Matrix
• Restricted Maximum Likelihood
• Genetic Association analysis

More advanced powers

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
• 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 to pick starting values
• Leave them at zero
• Make an educated guess
• Use mxAutoStart
• Error Status Codes

How do I plot results?

• Graphical output

Misc

• Cloud & big data
• Brownie baking
• Donating money
• Retro Mx