Extended Structural Equation Modelling
Example Factor Analysis Data for Scaling the Model
Indicator with marginal Negative Binomial distribution
Indicator with marginal Poisson distribution
MxMatrix Class
Create MxMatrix Object
Estimate Modification Indices for MxModel Objects
DEPRECATED: Create MxMLObjective Object
Information-Theoretic Model-Averaging and Multimodel Inference
MxModel Class
Create MxModel Object
mxNormalQuantiles
Set or Clear an Optimizer Option
An optional character
A character, integer, or NULL
An optional data.frame
An optional data.frame or matrix
An optional integer
An optional logical
An optional matrix
An optional numeric
Assess whether potential parameters should be freed using parametric b...
Create List of Paths
Example regression data with correlated predictors
On-Demand Parallel Apply
imxGetSlotDisplayNames
imxHasConstraint
imxHasDefinitionVariable
imxHasNPSOL
imxHasOpenMP
imxHasThresholds
imxHasWLS
imxIdentifier
Are submodels independent?
imxInitModel
imxIsDefinitionVariable
imxIsMultilevel
imxIsPath
imxIsStateSpace
imxLocateFunction
imxLocateIndex
imxLocateLabel
Test thread-safe output code
imxLookupSymbolTable
imxModelBuilder
imxModelTypes
imxMpiWrap
Run an classic mx script
imxPenaltyTypes
imxPPML
imxPPML.Test.Battery
imxPPML.Test.Test
imxPreprocessModel
imxReplaceMethod
Replace parts of a model
imxReplaceSlot
Report backend progress
imxReservedNames
imxReverseIdentifier
omxCheckNamespace
Create a matrix
Matrix exponential
Valid types of data that can be contained by MxData
imxDefaultGetSlotDisplayNames
Deparse for MxObjects
Are submodels dependence?
imxDetermineDefaultOptimizer
A C implementation of dmvnorm
imxEvalByName
imxExtractMethod
imxExtractNames
imxExtractReferences
imxExtractSlot
Remove hierarchical structure from model
Freeze model
imxGenerateLabels
imxGenerateNamespace
imxGenericModelBuilder
imxGenSwift
Resize an MxMatrix while preserving entries
imxGetNumThreads
omxGetBootstrapReplications
omxGetNPSOL
imxVariableTypes
imxVerifyMatrix
imxVerifyModel
imxVerifyName
imxVerifyReference
Calculate confidence intervals without re-doing the primary optimizati...
omxQuotes
omxRAMtoML
Read a GCTA-Format Binary GRM into R.
Convert a numeric or character vector into an optimizer status code fa...
BaseCompute
Bollen Data on Industrialization and Political Democracy
Vectorize By Column
Demonstration data for a one factor model
Demonstration data for a two factor model
Extract Diagonal of a Matrix
An S4 base class for discrete marginal distributions
Example Factor Analysis Data
Example twin extended kinship data: DZ female data
Example twin extended kinship data: DZ Male data
Example twin extended kinship data: DZ opposite sex twins
Eigenvector/Eigenvalue Decomposition
Bivariate twin data, wide-format from Classic Mx Manual
Bivariate twin data, long-format from Classic Mx Manual
Example Factor Analysis Data for Scaling the Model
Add dependencies
Holzinger & Swineford (1939) Ability in 301 children from 2 schools
Add a dependency
imxAutoOptionValue
imxCheckMatrices
imxCheckVariables
Condense/de-condense slots of an MxMatrix
imxConstraintRelations
imxConvertIdentifier
imxConvertLabel
imxConvertSubstitution
imxRobustSE
imxRowGradients
imxSameType
imxSeparatorChar
imxSfClient
imxSimpleRAMPredicate
Sparse symmetric matrix invert
imxSquareMatrix
imxSymmetricMatrix
imxTypeName
imxUntitledName
imxUntitledNumber
imxUntitledNumberReset
imxUpdateModelValues
Calculate Chi Square for a WLS Model
Calculate Standard Errors for a WLS Model
Joint Ordinal and continuous variables to be modeled together
Example data for multiple regression among latent variables
Example data for multiple regression among latent variables
Create a fit function used to fit multiple-group models
Respondent-soldiers on four dichotomous items
Matrix logarithm
Data for multiple regression
MxAlgebra Class
Create MxAlgebra Object
MxAlgebraFormula
Create MxAlgebra object from a string
DEPRECATED: Create MxAlgebraObjective Object
Create MxLISRELObjective Object
An optional list
mxMakeNames
Automatically set starting values for an MxModel
mxAvailableOptimizers
MxBaseExpectation
MxBaseFitFunction
MxBaseNamed
MxBaseObjectiveMetaData
Repeatedly estimate model using resampling with replacement
Evaluate Values in a bootstrapped MxModel
Bootstrap distribution of standardized RAM path coefficients
MxBounds Class
Create MxBounds Object
A character, list or NULL
A character or logical
A character or integer
Check that a model is locally identified
MxCI Class
Create mxCI Object
The MxCompare Class
Likelihood ratio test
MxCompute
Repeatedly estimate model using resampling with replacement
Numerically estimate the Jacobian with respect to free parameters
Log parameters and state to disk or memory
Find likelihood-based confidence intervals
Default compute plan
Fit a model using DLR's (1977) Expectation-Maximization (EM) algorithm
Generate data
Optimize parameters using a gradient descent optimizer
Compute the quality of the Hessian
Repeatedly invoke a series of compute objects until change is less tha...
Load contextual data to supplement checkpoint
Load columns into an MxData object
Load data from CSV files directly into the backend
Repeatedly invoke a series of compute objects
Optimize parameters using a variation of the Nelder-Mead algorithm.
Optimize parameters using the Newton-Raphson algorithm
Compute nothing
Numerically estimate Hessian using Richardson extrapolation
Class "MxFitFunctionGREML"
Compute something once
Regularize parameter estimates
Report derivatives
Report expectation
Invoke a series of compute objects in sequence
Reset parameter starting values
Optimization using generalized simulated annealing
Compute standard errors
Execute a sub-compute plan, catching errors
Create MxFitFunctionGREML Object
Create MxFitFunctionML Object
Like simplify2array but works with vectors of different lengths
Repeatedly attempt a compute plan until successful
Class "MxConstraint"
Create MxConstraint Object
MxData Class
Create MxData Object
Create dynamic data
Create static data
Create legacy MxData Object for Least Squares (WLS, DWLS, ULS) Analyse...
Determine whether a dataset will have weights and summary statistics f...
MxDirectedGraph
Evaluate Values in MxModel
Evaluate an algebra on an abscissa grid and collect column results
Create a Bock & Aitkin (1981) expectation
Class "MxExpectationGREML"
Create MxExpectationGREML Object
Hidden Markov expectation
Create MxExpectationLISREL Object
Mixture expectation
Create MxExpectationNormal Object
Create an MxExpectationRAM Object
Create an MxExpectationStateSpace Object
Create an MxExpectationStateSpace Object
MxExpectation
Fail-safe Factors
Estimate factor scores and standard errors
DEPRECATED: Create MxFIMLObjective Object
MxFitFunction
Create MxFitFunctionAlgebra Object
Create MxFitFunctionR Object
Create an MxFitFunctionRow Object
Create MxFitFunctionWLS Object
MxFlatModel
Generate data based on an mxModel (or a data.frame)
Extract the component from a model's expectation
Helper Function for Structuring GREML Data
MxInterval
Jiggle parameter values.
Estimate Kalman scores and error covariance matrices
MxLISRELModel
Perform Pearson Aitken selection
MxPenalty
This function creates a penalty object
mxPenaltyElasticNet
mxPenaltyLASSO
mxPenaltyRidge
Make multiple attempts to run a model
mxPenaltySearch
mxPenaltyZap
Power curve
MxRAMGraph
MxRAMModel
DEPRECATED: Create MxRAMObjective Object
Rename a model or submodel
Standardize RAM models' path coefficients
Create List of Thresholds
List Currently Available Model Types
Restore model state from a checkpoint file
Return random classic Mx error message
DEPRECATED: Create MxRObjective Object
DEPRECATED: Create MxRowObjective Object
Run an OpenMx model
Save model state to a checkpoint file
Compute standard errors in OpenMx
Reset global options to the default
Returns Current Version String
A package_version or character
Example data with autoregressively related columns
Example 500-row dataset with 12 generated variables
Data for a growth mixture model with the true class membership
Data for a growth mixture model
Data for a linear latent growth curve model
Example regression data with correlated predictors
Duplicate of twinData
Example twin extended kinship data: MZ female twins
Example twin extended kinship data: MZ Male data
Named Entities
Twin data from a nuclear family design
numeric Hessian data 1
numeric Hessian data 2
All Interval Multivariate Normal Integration
Assign First Available Values to Model Parameters
Estimate summary statistics used by the WLS fit function
Make Brownies in OpenMx
Build the model used for mxAutoStart
Approximate Equality Testing Function
Equality Testing Function
Correct Error Message Function
Exact Equality Testing Function
Set Equality Testing Function
Boolean Equality Testing Function
Correct Warning Message Function
Approximate Percent Equality Testing Function
omxConstrainMLThresholds
Construct default compute plan
omxDetectCores
Fetch Model Parameters
omxGetRAMDepth
Show RAM Model in Graphviz Format
omxHasDefaultComputePlan
On-Demand Parallel Lapply
Get the location (model, matrix, row, column) and other info for a par...
Get the RMSEA with confidence intervals from model
Logical mxAlgebra() operators
Estimate the Jacobian of manifest model with respect to parameters
MxMatrix operations
Multivariate Normal Integration
Remove all instances of data from a model
omxNameAnonymousParameters
On-Demand Parallel Sapply
Create Reference (Saturated and Independence) Models
Filter rows and columns from an mxMatrix
Assign Model Parameters
Internal OpenMx algebra operations
OpenMx: An package for Structural Equation Modeling and Matrix Algebra...
Oscillator Data for Latent Differential Equations
Strict Half-vectorization
predict
method for MxModel
objects
Vectorize By Row
Model Summary
trace
Twin biometric data (Practice cleaning: "." for missing data, wrong da...
Create Diagonal Matrix From Vector
Half-vectorization
Inverse Half-vectorization
Inverse Strict Half-vectorization
Create structural equation models that can be manipulated programmatically. Models may be specified with matrices or paths (LISREL or RAM) Example models include confirmatory factor, multiple group, mixture distribution, categorical threshold, modern test theory, differential Fit functions include full information maximum likelihood, maximum likelihood, and weighted least squares. equations, state space, and many others. Support and advanced package binaries available at <http://openmx.ssri.psu.edu>. The software is described in Neale, Hunter, Pritikin, Zahery, Brick, Kirkpatrick, Estabrook, Bates, Maes, & Boker (2016) <doi:10.1007/s11336-014-9435-8>.
Useful links