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