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simsem (version 0.2-0)

SIMulated Structural Equation Modeling.

Description

This package can be used to generate data using the structural equation modeling framework. This package is tailored to use those simulated data for various purposes, such as model fit evaluation, power analysis, or missing data handling and planning.

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Install

install.packages('simsem')

Monthly Downloads

1,283

Version

0.2-0

License

GPL (>= 2)

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Repository

https://github.com/simsem/simsem/wiki

Maintainer

Sunthud Pornprasertmanit

Last Published

May 18th, 2012

Functions in simsem (0.2-0)

blankParameters

Change all elements in the non-null objects to be all NAs.

findFactorResidualVar

Find factor residual variances from regression coefficient matrix, factor (residual) correlations, and total factor variances

checkInputValue

Check the value argument in the matrix, symmetric matrix, or vector objects

Check whether a matrix is a possible correlation matrix

Create a free parameters vector with a starting values in a vector object

Run one replication within a big simulation study

Create random chi-squared distribution object

Set of model misspecification for Path analysis model.

The constructor of the parameter result object

Create simVector that save free parameters and starting values, as well as fixed values

Create random Poisson distribution object

Create symmetric simMatrix that save free parameters and starting values, as well as fixed values

Finding skewness

Provide summary of parameter estimates and standard error across replications

writeLavaanIndividualConstraint

Write a lavaan code for a given equality constraint for each parameter

Calculate the weighted mean of a variable

Class "SimData"

SimGenLabels-class

Class "SimGenLabels"

SimVector-class

Vector object: Random parameters vector

SimModelMIOut-class

Class "SimModelMIOut"

Change an element in SimMatrix, SymMatrix, or SimVector.

Extract a part of an object

createFreeParameters

Create a free parameters object from a model specification

isMeanConstraint

Check whether all rownames in a constraint matrix containing symbols of means vectors

Impose MAR, MCAR, planned missingness, or attrition on a data set

Function to pool imputed results

Run data by the model object by the lavaan package

Create simResult.

Find starting values by averaging random numbers

Tag names to each element

writeLavaanNullCode

Write a lavaan code for a null model

vectorizeObject

Change an object to a vector with labels

Provide short summary of an object.

SimREqualCon-class

Class "SimREqualCon"

constrainMatrices

Impose an equality constraint in an object

Expand the set of intercept and covariance matrices into the set of intercept/mean and covariance/correlation/variance objects

Find power in rejecting alternative models based on fit indices criteria

Check whether a vector object is default

Search for the keywords and check whether the specified text match one in the name vector

Find population misfit by sufficient statistics

reduceConstraint

Reduce the model constraint to data generation parameterization to analysis model parameterization.

Create random beta distribution object

Construct a SimMissing object to create data with missingness and analyze missing data.

Create function object

Standardize the parameter estimates within an object

Create a set of matrices of parameters for analyzing data that belongs to SEM model

Validate whether the regression coefficient (or loading) matrix is good

SimFunction-class

Class "SimFunction"

Collapse all exogenous variables and put all in endogenous side only.

countFreeParameters

Count how many free parameters in the target object

Create data from model parameters

Fill in other objects based on the parameter values of current objects

Calculate the k-statistic of a variable

isVarianceConstraint

Check whether all rownames in a constraint matrix containing symbols of variance vectors

Make parameter names for each element in matrices or vectors or the name for the whole object

Make a product of indicators using mean centering or double-mean centering

Plot the population misfit in parameter result object

findRecursiveSet

Group variables regarding the position in mediation chain

Build a scatterplot with overlaying line of quantiles of predicted values

Run a particular object in simsem package.

residualCovariate

Residual centered all target indicators by covariates

Create random log normal distribution object

Create random logistic distribution object

Set of model misspecification for CFA model.

Create simModel from model specification and be ready for data analysis.

Set of model misspecification for SEM model.

Create random geometric distribution object

Create a set of matrices of parameter and parameter values to generate and analyze data that belongs to CFA model.

SimResult-class

Class "SimResult"

combineLatentCorExoEndo

Combine exogenous factor correlation and endogenous factor correlation into a single matrix

combineMeasurementErrorExoEndo

Combine measurement error correlation from the exogenous and endogenous sides into a single matrix

Function to pool chi-square statistics from the result from multiple imputation

Multiply impute and analyze data using lavaan

List of all keywords used in the simsem package

loadingFromAlpha

Find standardized factor loading from coefficient alpha

Create random binomial distribution object

Create a set of matrices of parameter and parameter values to generate and analyze data that belongs to SEM model

Export the distribution object to a function command in text that can be evaluated directly.

Create random t distribution object

Create a set of matrices of parameters for analyzing data that belongs to Path analysis model

SimEqualCon-class

Class "SimEqualCon"

SimDataOut-class

Class "SimDataOut"

SymMatrix-class

Symmetric matrix object: Random parameters symmetric matrix

SimResultParam-class

Class "SimResultParam"

combinePathExoEndo

Combine the regression coefficient matrices

drawParametersMisspec

Create parameter sets (with or without model misspecification) from the parameter with or without misspecification set

Create parameter sets (with or without model misspecification) from the data object

findFactorIntercept

Find factor intercept from regression coefficient matrix and factor total means

SimMisspec-class

Class "SimMisspec"

extractOpenMxFit

Extract the fit indices reported by the OpenMx result

findIndIntercept

Find indicator intercepts from factor loading matrix, total factor mean, and indicator mean.

Find indicator total means from factor loading matrix, total factor mean, and indicator intercept.

findPossibleFactorCor

Find the appropriate position for freely estimated correlation (or covariance) given a regression coefficient matrix

Check whether the object is the NULL type of that class

findIndResidualVar

Find indicator residual variances from factor loading matrix, total factor covariance, and total indicator variances.

Extract the data generation population model underlying an object

Function to pool imputed results that saved in a matrix format

Find the discrepancy value between two means and covariance matrices

Reassign the name of equality constraint

Reduce the model constraint to data generation parameterization to analysis model parameterization.

Create random hypergeometric distribution object

validateCovariance

Validate whether all elements provides a good covariance matrix

Create random uniform distribution object

Class "SimSet"

Calculate central moments of a variable

combineLoadingExoEndo

Combine factor loading from the exogenous and endogenous sides into a single matrix

Class "VirtualRSet", "SimLabels" and "SimRSet"

Convert a covariance matrix to a correlation matrix

Find factor total means from regression coefficient matrix and factor intercept

extractVectorNames

Extract a vector of parameter names based on specified elements

extractLavaanFit

Extract fit indices from the lavaan object

findFactorTotalCov

Find factor total covariance from regression coefficient matrix, factor residual covariance

findIndTotalVar

Find indicator total variances from factor loading matrix, total factor covariance, and indicator residual variances.

Find p-values (1 - percentile)

Calculate population misfit

Provide basic summary of each object if that object is not NULL.

Create random Cauchy distribution object

writeLavaanCode

Write a lavaan code given the matrices of free parameter

Create a data distribution object.

Create a set of matrices of parameters for analyzing data that belongs to CFA model.

writeLavaanConstraint

Write a lavaan code for a given set of equality constraints

SimDataDist-class

Class "SimDataDist"

SimMatrix-class

Matrix object: Random parameters matrix

Class "SimParam"

Provide a comparison of nested models across replications

SimModelOut-class

Class "SimModelOut"

VirtualDist-class

Distribution Objects

createImpliedMACS

Create model implied mean vector and covariance matrix

extractMatrixNames

Extract a vector of parameter names based on specified rows and columns

Build a persepctive plot or contour plot of a quantile of predicted values

Plot sampling distributions of fit indices

Plot sampling distributions of fit indices that visualize power

Draw actual parameters and model misspecification

Create random gamma distribution object

Create random Weibull distribution object

Create random normal distribution object

setOpenMxObject

Rearrange starting values for OpenMx

MatrixSet-class

Class "MatrixSet"

Create a constant vector object

SimMissing-class

Class "SimMissing"

Extract only converged replications in the result object

Class "SimModel"

Find rows in a matrix that all elements are zero in non-fixed subset rows and columns.

Make a division on each element of the object

defaultStartingValues

Make ad hoc starting values

findFactorTotalVar

Find factor total variances from regression coefficient matrix, factor (residual) correlations, and factor residual variances

continuousPower

Find power of model parameters when simulations have randomly varying parameters

Make a subtraction of each element in an object

Plot a distribution of a distribution object or data distribution object

Plot overlapping histograms

Validate whether the drawn parameters are good.

Create random F distribution object

Find fit indices from the discrepancy values of the target model and null models.

Find cutoff given a priori alpha level

Check whether the object contains any random parameters

Combine by summing or binding two objects together.

Build a result object from analyzing real data

Create a set of matrices of parameter and parameter values to generate and analyze data that belongs to Path analysis model

summaryPopulation

Summarize the data generation population model underlying an object

Equality Constraint Object

Create random exponential distribution object

Transform the analysis model object into the object for data generation

Set the data generation population model underlying an object

Create simMatrix that save free parameters and starting values, as well as fixed values

Finding excessive kurtosis

Count the number of elements in the sufficient statistics

Create random negative binomial distribution object