Public Classes and Functions

This section will list all classes and functions relating to all objects in this package except the distribution objects.

Classes

• SimData Save information for data simulation and can create data by run function.
• SimDataDist Provide the distribution of a dataset.
• SimDataOut Provide the simulated dataset and population behind the generated dataset.
• SimEqualCon Save information of equality constraints
• SimFunction Use for data transformation while running a simulation study
• SimMatrix Represent a matrix in SEM model containing free parameters, fixed values, and starting values.
• SimMissing Save missing information to impose on the complete dataset
• SimMisspec Save misspecification model adding on top of true model specification.
• SimModel Save information for analysis model
• SimModelMIOut Save the analysis results from a single multiply imputed dataset
• SimModelOut Save the analysis results from a single dataset
• SimParam Contain a set of vectors and matrices saving free parameters
• SimResult Provide the parameter values used in all replications in a simulation study
• SimResultParam Provide the result of a simulation study
• SimSet Contain a set of vectors and matrices saving free parameters, fixed values, and starting values
• SimVector Represent a vector in SEM model containing free parameters, fixed values, and starting values.
• SymMatrix Represent a symmetric matrix in SEM model containing free parameters, fixed values, and starting values.

S4 Functions

• adjust Change an element in matrix, symmetric matrix or vector objects. Available Classes: SimMatrix, SymMatrix, SimVector
• anova Provide a comparison of nested models and nonnested models across replications. Available Classes: SimModelOut, SimResult
• createImpliedMACS Create model implied mean vector and covariance matrix. Available Classes: SimModelOut, SimModelMIOut, SimDataOut
• extract Extract a part of an object. Available Classes: vector, matrix, SimMatrix, SimVector, SimSet, SimDataDist, SimParam
• getCutoff Find fit indices cutoff given a priori alpha level. Available Classes: SimResult
• getPopulation Extract the data generation population model underlying an object. Available Classes: SimDataOut, SimModelOut, SimResult
• getPowerFit Find power in rejecting alternative models based on fit indices criteria. Available Classes: SimResult
• kurtosis Finding excessive kurtosis. Available Classes: vector, VirtualDist
• plotCutoff Plot sampling distributions of fit indices with fit indices cutoffs. Available Classes: SimResult
• plotDist Plot a distribution of a distribution object or data distribution object. Available Classes: SimDataDist
• plotPowerFit Plot sampling distributions of fit indices that visualize power of rejecting datasets underlying misspecified models. Available Classes: SimResult
• popMisfit Calculate population misfit. Available Classes: (matrix, matrix), (list, list), (SimRSet, SimRSet), (MatrixSet, MatrixSet), (SimSet, SimMisspec)
• pValue Find p-values (1 - percentile). Available Classes: (numeric, vector), (numeric, data.frame), (SimModelOut, SimResult)
• run Run an object in this package. Available Classes: SimData, SimMatrix, SimSet, SimMisspec, SimModel, SimVector, SymMatrix, SimMissing, SimDataDist
• runFit Build a Monte Carlo simulation that the data-generation parameters are from the result of analyzing real data. Available Classes: SimModel, SimModelOut
• setPopulation Set the data generation population model underlying an object. Available Classes: (SimResult, data.frame), (SimResult, SimSet), (SimResult, VirtualRSet), (SimModelOut, SimRSet), (SimModelOut, SimSet)
• simData Create a data object. Available Classes: SimSet, SimModelOut
• simModel Create a model object. Available Classes: SimSet, SimParam
• skew Find skewness. Available Classes: vector, VirtualDist
• summary Summarize an object. Available Classes: All classes
• summaryParam Provide summary of parameter estimates and standard error across replications. Available Classes: SimResult
• summaryPopulation Summarize the data generation population model underlying an object. Available Classes: SimDataOut, SimModelOut, SimResult
• summaryShort Provide short summary of an object. Available Classes: All classes
• toFunction Export the distribution object to a function command in text that can be evaluated directly.. Available Classes: VirtualDist

S3 Functions

• continuousPower Find power of model parameters when simulations have randomly varying parameters
• findFactorIntercept Find factor intercept from regression coefficient matrix and factor total means
• findFactorMean Find factor total means from regression coefficient matrix and factor intercept
• findFactorResidualVar Find factor residual variances from regression coefficient matrix, factor (residual) correlations, and total factor variances
• findFactorTotalCov Find factor total covariance from regression coefficient matrix, factor residual covariance
• findFactorTotalVar Find factor total variances from regression coefficient matrix, factor (residual) correlations, and factor residual variances
• findIndIntercept Find indicator intercepts from factor loading matrix, total factor mean, and indicator mean.
• findIndMean Find indicator total means from factor loading matrix, total factor mean, and indicator intercept.
• findIndResidualVar Find indicator residual variances from factor loading matrix, total factor covariance, and total indicator variances.
• findIndTotalVar Find indicator total variances from factor loading matrix, total factor covariance, and indicator residual variances.
• findPossibleFactorCor Find the appropriate position for freely estimated correlation (or covariance) given a regression coefficient matrix
• findPower Find a value of independent variables that provides a given value of power.
• findRecursiveSet Group variables regarding the position in mediation chain
• getPower Find power of model parameters
• imposeMissing Impose MAR, MCAR, planned missingness, or attrition on a data set
• indProd Make a product of indicators using mean centering or double-mean centering
• loadingFromAlpha Find standardized factor loading from coefficient alpha assuming that all items have equal loadings.
• miPoolChi The function combines likelihood ratio chi-square statistics from an analysis of multiply imputed data sets
• miPoolVector The function takes parameter estimates and standard errors of each imputed result and returns pooled parameter estimates and standard errors.
• plotMisfit Plot a histogram of the amount of population misfit in parameter result object or the scatter plot of the relationship between misspecified parameter and the population misfit
• plotPower Make a power plot of a parameter given varying parameters (e.g., sample size, percent missing completely at random, or random parameters in the model)
• popDiscrepancy Find the discrepancy value between two means and covariance matrices
• popMisfitMACS Find the value quantifying the amount of population misfit
• residualCovariate Residual centered all target indicators by covariates
• runMI Multiply impute and analyze data
• simEqualCon Create an equality constraint object
• simFunction Create a function object
• simMatrix Create a matrix object
• simMissing Create a missing object
• simMisspecCFA Set of model misspecification for CFA model
• simMisspecPath Set of model misspecification for path analysis model.
• simMisspecSEM Set of model misspecification for SEM model.
• simParamCFA Set of model free parameters for CFA model.
• simParamPath Set of model free parameters for path analysis model.
• simParamSEM Set of model free parameters for SEM model.
• simResult Create a result from simulation study
• simResultParam Create sets of parameters used in a simulation study
• simSetCFA Set of model free parameters and parameter values for CFA model.
• simSetPath Set of model free parameters and parameter values for path analysis model.
• simSetSEM Set of model free parameters and parameter values for SEM model.
• simVector Create a vector object
• symMatrix Create a symmetric matrix object