| Data analysis using the model specification | analyze |
| Provide a comparison of nested models and nonnested models across replications | anova,SimResult-method |
| Specify matrices for Monte Carlo simulation of structural equation models | bind binds |
| Create a data distribution object. | bindDist |
| Extract parameter estimates from a simulation result | coef,SimResult-method |
| Combine result objects | combineSim |
| Find coverage rate of model parameters when simulations have randomly varying parameters | continuousCoverage |
| Find power of model parameters when simulations have randomly varying parameters | continuousPower |
| Create data from a set of drawn parameters. | createData |
| Draw parameters from a 'SimSem' object. | draw |
| Shortcut for data analysis template for simulation. | estmodel estmodel.cfa estmodel.path estmodel.sem |
| Export data sets for analysis with outside SEM program. | exportData |
| Find a value of independent variables that provides a given value of coverage rate | findCoverage |
| Find factor intercept from regression coefficient matrix and factor total means | findFactorIntercept |
| Find factor total means from regression coefficient matrix and factor intercept | findFactorMean |
| Find factor residual variances from regression coefficient matrix, factor (residual) correlations, and total factor variances | findFactorResidualVar |
| Find factor total covariance from regression coefficient matrix, factor residual covariance | findFactorTotalCov |
| Find factor total variances from regression coefficient matrix, factor (residual) correlations, and factor residual variances | findFactorTotalVar |
| Find indicator intercepts from factor loading matrix, total factor mean, and indicator mean. | findIndIntercept |
| Find indicator total means from factor loading matrix, total factor mean, and indicator intercept. | findIndMean |
| Find indicator residual variances from factor loading matrix, total factor covariance, and total indicator variances. | findIndResidualVar |
| Find indicator total variances from factor loading matrix, total factor covariance, and indicator residual variances. | findIndTotalVar |
| Find the appropriate position for freely estimated correlation (or covariance) given a regression coefficient matrix | findPossibleFactorCor |
| Find a value of independent variables that provides a given value of power. | findPower |
| Group variables regarding the position in mediation chain | findRecursiveSet |
| Generate data using SimSem template | generate |
| Find confidence interval width | getCIwidth |
| Find coverage rate of model parameters | getCoverage |
| Find fit indices cutoff given a priori alpha level | getCutoff |
| Find fit indices cutoff for nested model comparison given a priori alpha level | getCutoffNested |
| Find fit indices cutoff for non-nested model comparison given a priori alpha level | getCutoffNonNested |
| Get extra outputs from the result of simulation | getExtraOutput |
| Extract the data generation population model underlying a result object | getPopulation |
| Find power of model parameters | getPower |
| Find power in rejecting alternative models based on fit indices criteria | getPowerFit |
| Find power in rejecting nested models based on the differences in fit indices | getPowerFitNested |
| Find power in rejecting non-nested models based on the differences in fit indices | getPowerFitNonNested getPowerFitNonNested,SimResult,SimResult,missing-method getPowerFitNonNested,SimResult,SimResult,vector-method getPowerFitNonNested-methods |
| Impose MAR, MCAR, planned missingness, or attrition on a data set | impose imposeMissing |
| Extract information from a simulation result | inspect inspect,SimResult-method |
| Find the likelihood ratio (or Bayes factor) based on the bivariate distribution of fit indices | likRatioFit |
| Specifying the missing template to impose on a dataset | miss |
| Data generation template and analysis template for simulation. | model model.cfa model.path model.sem |
| Build the data generation template and analysis template from the lavaan result | model.lavaan |
| Test whether all objects are equal | multipleAllEqual |
| Plot a confidence interval width of a target parameter | plotCIwidth |
| Make a plot of confidence interval coverage rates | plotCoverage |
| Plot sampling distributions of fit indices with fit indices cutoffs | plotCutoff |
| Plot sampling distributions of the differences in fit indices between nested models with fit indices cutoffs | plotCutoffNested |
| Plot sampling distributions of the differences in fit indices between non-nested models with fit indices cutoffs | plotCutoffNonNested |
| Plot a distribution of a data distribution object | plotDist |
| Visualize the missing proportion when the logistic regression method is used. | plotLogitMiss |
| Plot the population misfit in the result object | plotMisfit |
| Make a power plot of a parameter given varying parameters | plotPower |
| Plot sampling distributions of fit indices that visualize power of rejecting datasets underlying misspecified models | plotPowerFit |
| Plot power of rejecting a nested model in a nested model comparison by each fit index | plotPowerFitNested |
| Plot power of rejecting a non-nested model based on a difference in fit index | plotPowerFitNonNested |
| Find the discrepancy value between two means and covariance matrices | popDiscrepancy |
| Find population misfit by sufficient statistics | popMisfitMACS |
| Find p-values (1 - percentile) by comparing a single analysis output from the result object | pValue |
| Find p-values (1 - percentile) for a nested model comparison | pValueNested |
| Find p-values (1 - percentile) for a non-nested model comparison | pValueNonNested |
| Draw values from vector or matrix objects | rawDraw |
| Set the data generation population model underlying an object | setPopulation |
| Run a Monte Carlo simulation with a structural equation model. | sim |
| Class '"SimDataDist"': Data distribution object | plotDist,SimDataDist-method SimDataDist-class summary,SimDataDist-method |
| Matrix object: Random parameters matrix | SimMatrix-class summary,SimMatrix-method summaryShort,SimMatrix-method |
| Class '"SimMissing"' | SimMissing-class summary,SimMissing-method |
| Class '"SimResult"': Simulation Result Object | SimResult-class summary,SimResult-method summaryShort,SimResult-method |
| Class '"SimSem"' | SimSem-class summary,SimSem-method |
| Vector object: Random parameters vector | SimVector-class summary,SimVector-method summaryShort,SimVector-method |
| Provide a comparison between the characteristics of convergent replications and nonconvergent replications | summaryConverge |
| Provide summary of model fit across replications | summaryFit |
| Provide summary of the population misfit and misspecified-parameter values across replications | summaryMisspec |
| Provide summary of parameter estimates and standard error across replications | summaryParam |
| Summarize the population model used for data generation underlying a result object | summaryPopulation |
| Summary of a seed number | summarySeed |
| Provide short summary of an object. | summaryShort summaryShort,ANY-method summaryShort,matrix-method summaryShort,vector-method summaryShort-methods |
| Time summary | summaryTime |
