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A B C D E F G I K L M N O P R S T V W
| adjust | Change an element in 'SimMatrix', 'SymMatrix', or 'SimVector'. |
| adjust-method | Change an element in 'SimMatrix', 'SymMatrix', or 'SimVector'. |
| adjust-methods | Change an element in 'SimMatrix', 'SymMatrix', or 'SimVector'. |
| anova-method | Provide a comparison of nested models and nonnested models across replications |
| blankParameters | Change all elements in the non-null objects to be all NAs. |
| centralMoment | Calculate central moments of a variable |
| checkInputValue | Check the value argument in the matrix, symmetric matrix, or vector objects |
| checkInputValueVector | Check the value argument in the matrix, symmetric matrix, or vector objects |
| clean | Extract only converged replications in the result objects |
| cleanSimResult | Extract only converged replications in the result object |
| collapseExo | Collapse all exogenous variables and put all in endogenous side only. |
| combineLatentCorExoEndo | Combine exogenous factor correlation and endogenous factor correlation into a single matrix |
| combineLoadingExoEndo | Combine factor loading from the exogenous and endogenous sides into a single matrix |
| combineMeasurementErrorExoEndo | Combine measurement error correlation from the exogenous and endogenous sides into a single matrix |
| combineObject | Combine by summing or binding two objects together. |
| combineObject-method | Combine by summing or binding two objects together. |
| combineObject-methods | Combine by summing or binding two objects together. |
| combinePathExoEndo | Combine the regression coefficient matrices |
| constantVector | Create a constant vector object |
| constrainMatrices | Impose an equality constraint in an object |
| constrainMatrices-method | Impose an equality constraint in an object |
| constrainMatrices-methods | Impose an equality constraint in an object |
| continuousPower | Find power of model parameters when simulations have randomly varying parameters |
| countFreeParameters | Count how many free parameters in the target object |
| countFreeParameters-method | Count how many free parameters in the target object |
| countFreeParameters-methods | Count how many free parameters in the target object |
| countMACS | Count the number of elements in the sufficient statistics |
| cov2corMod | Convert a covariance matrix to a correlation matrix |
| createData | Create data from model parameters |
| createFreeParameters | Create a free parameters object from a model specification |
| createImpliedMACS | Create model implied mean vector and covariance matrix |
| createImpliedMACS-method | Class '"SimDataOut"' |
| createImpliedMACS-method | Class '"SimModelOut"' |
| createImpliedMACS-method | Create model implied mean vector and covariance matrix |
| createImpliedMACS-methods | Create model implied mean vector and covariance matrix |
| defaultStartingValues | Make ad hoc starting values |
| divideObject | Make a division on each element of the object |
| divideObject-method | Make a division on each element of the object |
| divideObject-methods | Make a division on each element of the object |
| drawParameters | Create parameter sets (with or without model misspecification) from the data object |
| drawParametersMisspec | Create parameter sets (with or without model misspecification) from the parameter with or without misspecification set |
| expandMatrices | Expand the set of intercept and covariance matrices into the set of intercept/mean and covariance/correlation/variance objects |
| extract | Extract a part of an object |
| extract-method | Class '"SimDataDist"' |
| extract-method | Matrix object: Random parameters matrix |
| extract-method | Class '"SimSet"' |
| extract-method | Vector object: Random parameters vector |
| extract-method | Extract a part of an object |
| extract-methods | Extract a part of an object |
| extractLavaanFit | Extract fit indices from the lavaan object |
| extractMatrixNames | Extract a vector of parameter names based on specified rows and columns |
| extractOpenMxFit | Extract the fit indices reported by the 'OpenMx' result |
| extractVectorNames | Extract a vector of parameter names based on specified elements |
| fillParam | Fill in other objects based on the parameter values of current objects |
| find2Dhist | Fit the 2D Kernel Density Estimate |
| 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. |
| findphist | Find the density (likelihood) of a pair value in 2D Kernel Density Estimate |
| 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 |
| findRowZero | Find rows in a matrix that all elements are zero in non-fixed subset rows and columns. |
| findTargetPower | Find a value of varying parameters that provides a given value of power. |
| fitMeasuresChi | Find fit indices from the discrepancy values of the target model and null models. |
| freeVector | Create a free parameters vector with a starting values in a vector object |
| getCondQtile | Get a quantile of a variable given values of predictors |
| getCutoff | Find fit indices cutoff given a priori alpha level |
| getCutoff-method | Find fit indices cutoff given a priori alpha level |
| getCutoff-methods | 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 |
| getKeywords | List of all keywords used in the 'simsem' package |
| getPopulation | Extract the data generation population model underlying an object |
| getPopulation-method | Class '"SimDataOut"' |
| getPopulation-method | Class '"SimModelOut"' |
| getPopulation-method | Class '"SimResult"' |
| getPopulation-method | Extract the data generation population model underlying an object |
| getPopulation-methods | Extract the data generation population model underlying an object |
| getPower | Find power of model parameters |
| getPowerFit | Find power in rejecting alternative models based on fit indices criteria |
| getPowerFit-method | Find power in rejecting alternative models based on fit indices criteria |
| getPowerFit-methods | 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 |
| getPowerFitNested-method | Find power in rejecting nested models based on the differences in fit indices |
| getPowerFitNested-methods | 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 |
| imposeMissing | Impose MAR, MCAR, planned missingness, or attrition on a data set |
| interpolate | Find the value of one vector relative to a value of another vector by interpolation |
| isCorMatrix | Check whether a 'matrix' is a possible correlation matrix |
| isDefault | Check whether a vector object is default |
| isMeanConstraint | Check whether all rownames in a constraint matrix containing symbols of means vectors |
| isNullObject | Check whether the object is the 'NULL' type of that class |
| isNullObject-method | Check whether the object is the 'NULL' type of that class |
| isNullObject-methods | Check whether the object is the 'NULL' type of that class |
| isRandom | Check whether the object contains any random parameters |
| isRandom-method | Check whether the object contains any random parameters |
| isRandom-methods | Check whether the object contains any random parameters |
| isVarianceConstraint | Check whether all rownames in a constraint matrix containing symbols of variance vectors |
| kStat | Calculate the _k_-statistic of a variable |
| kurtosis | Finding excessive kurtosis |
| kurtosis-method | Distribution Objects |
| kurtosis-method | Finding excessive kurtosis |
| kurtosis-methods | Finding excessive kurtosis |
| likRatioFit | Find the likelihood ratio (or Bayes factor) based on the bivariate distribution of fit indices |
| loadingFromAlpha | Find standardized factor loading from coefficient alpha |
| makeLabels | Make parameter names for each element in matrices or vectors or the name for the whole object |
| makeLabels-method | Make parameter names for each element in matrices or vectors or the name for the whole object |
| makeLabels-methods | Make parameter names for each element in matrices or vectors or the name for the whole object |
| matchKeywords | Search for the keywords and check whether the specified text match one in the name vector |
| MatrixSet-class | Class '"MatrixSet"' |
| miPool | Function to pool imputed results |
| miPoolChi | Function to pool chi-square statistics from the result from multiple imputation |
| miPoolVector | Function to pool imputed results that saved in a matrix format |
| MisspecSet-class | Class '"MatrixSet"' |
| multipleAllEqual | Test whether all objects are equal |
| NullDataFrame-class | Null Objects |
| NullMatrix-class | Null Objects |
| NullRSet-class | Null Objects |
| NullSimDataDist-class | Null Objects |
| NullSimEqualCon-class | Null Objects |
| NullSimFunction-class | Null Objects |
| NullSimMatrix-class | Null Objects |
| NullSimMissing-class | Null Objects |
| NullSimMisspec-class | Null Objects |
| NullSimREqualCon-class | Null Objects |
| NullSimSet-class | Null Objects |
| NullSimVector-class | Null Objects |
| NullSymMatrix-class | Null Objects |
| NullVector-class | Null Objects |
| overlapHist | Plot overlapping histograms |
| plot3DQtile | Build a persepctive plot or contour plot of a quantile of predicted values |
| plotCutoff | Plot sampling distributions of fit indices with fit indices cutoffs |
| plotCutoff-method | Plot sampling distributions of fit indices with fit indices cutoffs |
| plotCutoff-methods | 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 distribution object or data distribution object |
| plotDist-method | Class '"SimDataDist"' |
| plotDist-method | Distribution Objects |
| plotDist-methods | Plot a distribution of a distribution object or data distribution object |
| plotIndividualScatter | Plot an overlaying scatter plot visualizing the power of rejecting misspecified models |
| plotLogisticFit | Plot multiple logistic curves for predicting whether rejecting a misspecified model |
| plotMisfit | Plot the population misfit in parameter result object |
| plotOverHist | Plot multiple overlapping histograms |
| 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 |
| plotPowerFitDf | 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 |
| plotPowerSig | Plot multiple logistic curves given a significance result matrix |
| plotQtile | Build a scatterplot with overlaying line of quantiles of predicted values |
| plotScatter | Plot overlaying scatter plots visualizing the power of rejecting misspecified models |
| popDiscrepancy | Find the discrepancy value between two means and covariance matrices |
| popMisfit | Calculate population misfit |
| popMisfit-method | Calculate population misfit |
| popMisfit-methods | Calculate population misfit |
| popMisfitMACS | Find population misfit by sufficient statistics |
| predProb | Function to get predicted probabilities from logistic regression |
| printIfNotNull | Provide basic summary of each object if that object is not NULL. |
| pValue | Find p-values (1 - percentile) |
| pValue-method | Find p-values (1 - percentile) |
| pValue-methods | Find p-values (1 - percentile) |
| pValueCondCutoff | Find a p value when the target is conditional (valid) on a specific value of a predictor |
| pValueNested | Find p-values (1 - percentile) for a nested model comparison |
| pValueNonNested | Find p-values (1 - percentile) for a non-nested model comparison |
| pValueVariedCutoff | Find a p value when the cutoff is specified as a vector given the values of predictors |
| reassignNames | Reassign the name of equality constraint |
| reduceConstraint | Reduce the model constraint to data generation parameterization to analysis model parameterization. |
| reduceMatrices | Reduce the model constraint to data generation parameterization to analysis model parameterization. |
| revText | Reverse the proportion value by subtracting it from 1 |
| run | Run a particular object in 'simsem' package. |
| run-method | Class '"SimData"' |
| run-method | Class '"SimDataDist"' |
| run-method | Class '"SimFunction"' |
| run-method | Class '"SimGenLabels"' |
| run-method | Matrix object: Random parameters matrix |
| run-method | Class '"SimMissing"' |
| run-method | Class '"SimMisspec"' |
| run-method | Class '"SimModel"' |
| run-method | Class '"SimSet"' |
| run-method | Vector object: Random parameters vector |
| run-method | Symmetric matrix object: Random parameters symmetric matrix |
| run-method | Distribution Objects |
| run-method | Run a particular object in 'simsem' package. |
| run-methods | Run a particular object in 'simsem' package. |
| runFit | Build a Monte Carlo simulation that the data-generation parameters are from the result of analyzing real data |
| runFit-method | Build a Monte Carlo simulation that the data-generation parameters are from the result of analyzing real data |
| runFit-methods | Build a Monte Carlo simulation that the data-generation parameters are from the result of analyzing real data |
| runFitParam | Build a parameter result object that the data-generation parameters are from the result of analyzing real data |
| runFitParam-method | Build a parameter result object that the data-generation parameters are from the result of analyzing real data |
| runFitParam-methods | Build a parameter result object that the data-generation parameters are from the result of analyzing real data |
| runLavaan | Run data by the model object by the 'lavaan' package |
| runMI | Multiply impute and analyze data using lavaan |
| runMisspec | Draw actual parameters and model misspecification |
| runRep | Run one replication within a big simulation study |
| setOpenMxObject | Rearrange starting values for 'OpenMx' |
| setOpenMxObject-method | Rearrange starting values for 'OpenMx' |
| setOpenMxObject-methods | Rearrange starting values for 'OpenMx' |
| setPopulation | Set the data generation population model underlying an object |
| setPopulation-method | Class '"SimModelOut"' |
| setPopulation-method | Class '"SimResult"' |
| setPopulation-method | Set the data generation population model underlying an object |
| setPopulation-methods | Set the data generation population model underlying an object |
| simBeta | Create random beta distribution object |
| SimBeta-class | Distribution Objects |
| simBinom | Create random binomial distribution object |
| SimBinom-class | Distribution Objects |
| simCauchy | Create random Cauchy distribution object |
| SimCauchy-class | Distribution Objects |
| simChisq | Create random chi-squared distribution object |
| SimChisq-class | Distribution Objects |
| simData | Create a Data object |
| SimData-class | Class '"SimData"' |
| simData-method | Create a Data object |
| simData-methods | Create a Data object |
| simDataDist | Create a data distribution object. |
| SimDataDist-class | Class '"SimDataDist"' |
| SimDataOut-class | Class '"SimDataOut"' |
| simEqualCon | Equality Constraint Object |
| SimEqualCon-class | Class '"SimEqualCon"' |
| simExp | Create random exponential distribution object |
| SimExp-class | Distribution Objects |
| simF | Create random F distribution object |
| SimF-class | Distribution Objects |
| simFunction | Create function object |
| SimFunction-class | Class '"SimFunction"' |
| simGamma | Create random gamma distribution object |
| SimGamma-class | Distribution Objects |
| SimGenLabels-class | Class '"SimGenLabels"' |
| simGeom | Create random geometric distribution object |
| SimGeom-class | Distribution Objects |
| simHyper | Create random hypergeometric distribution object |
| SimHyper-class | Distribution Objects |
| SimLabels-class | Class '"VirtualRSet"', '"SimLabels"' and '"SimRSet"' |
| simLnorm | Create random log normal distribution object |
| SimLnorm-class | Distribution Objects |
| simLogis | Create random logistic distribution object |
| SimLogis-class | Distribution Objects |
| simMatrix | Create simMatrix that save free parameters and starting values, as well as fixed values |
| SimMatrix-class | Matrix object: Random parameters matrix |
| simMissing | Construct a SimMissing object to create data with missingness and analyze missing data. |
| SimMissing-class | Class '"SimMissing"' |
| SimMisspec-class | Class '"SimMisspec"' |
| 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. |
| simModel | Create a model object |
| SimModel-class | Class '"SimModel"' |
| simModel-method | Create a model object |
| simModel-methods | Create a model object |
| SimModelMIOut-class | Class '"SimModelMIOut"' |
| SimModelOut-class | Class '"SimModelOut"' |
| simNbinom | Create random negative binomial distribution object |
| SimNbinom-class | Distribution Objects |
| simNorm | Create random normal distribution object |
| SimNorm-class | Distribution Objects |
| SimParam-class | Class '"SimParam"' |
| simParamCFA | Create a set of matrices of parameters for analyzing data that belongs to CFA model. |
| simParamPath | Create a set of matrices of parameters for analyzing data that belongs to Path analysis model |
| simParamSEM | Create a set of matrices of parameters for analyzing data that belongs to SEM model |
| simPois | Create random Poisson distribution object |
| SimPois-class | Distribution Objects |
| SimREqualCon-class | Class '"SimREqualCon"' |
| simResult | Create simResult. |
| SimResult-class | Class '"SimResult"' |
| simResultParam | The constructor of the parameter result object |
| SimResultParam-class | Class '"SimResultParam"' |
| SimRSet-class | Class '"VirtualRSet"', '"SimLabels"' and '"SimRSet"' |
| SimSet-class | Class '"SimSet"' |
| simSetCFA | Create a set of matrices of parameter and parameter values to generate and analyze data that belongs to CFA model. |
| simSetPath | Create a set of matrices of parameter and parameter values to generate and analyze data that belongs to Path analysis model |
| simSetSEM | Create a set of matrices of parameter and parameter values to generate and analyze data that belongs to SEM model |
| simT | Create random t distribution object |
| SimT-class | Distribution Objects |
| simUnif | Create random uniform distribution object |
| SimUnif-class | Distribution Objects |
| simVector | Create simVector that save free parameters and starting values, as well as fixed values |
| SimVector-class | Vector object: Random parameters vector |
| simWeibull | Create random Weibull distribution object |
| SimWeibull-class | Distribution Objects |
| skew | Find skewness |
| skew-method | Distribution Objects |
| skew-method | Find skewness |
| skew-methods | Find skewness |
| sortList | Sort two objects in a list |
| standardize | Standardize the parameter estimates within an object |
| standardize-method | Standardize the parameter estimates within an object |
| standardize-methods | Standardize the parameter estimates within an object |
| startingValues | Find starting values by averaging random numbers |
| startingValues-method | Find starting values by averaging random numbers |
| startingValues-methods | Find starting values by averaging random numbers |
| subtractObject | Make a subtraction of each element in an object |
| subtractObject-method | Make a subtraction of each element in an object |
| subtractObject-methods | Make a subtraction of each element in an object |
| summary-method | Class '"MatrixSet"' |
| summary-method | Class '"SimData"' |
| summary-method | Class '"SimDataDist"' |
| summary-method | Class '"SimDataOut"' |
| summary-method | Class '"SimEqualCon"' |
| summary-method | Class '"SimFunction"' |
| summary-method | Matrix object: Random parameters matrix |
| summary-method | Class '"SimMissing"' |
| summary-method | Class '"SimMisspec"' |
| summary-method | Class '"SimModel"' |
| summary-method | Class '"SimModelOut"' |
| summary-method | Class '"SimParam"' |
| summary-method | Class '"SimREqualCon"' |
| summary-method | Class '"SimResult"' |
| summary-method | Class '"SimResultParam"' |
| summary-method | Class '"SimSet"' |
| summary-method | Vector object: Random parameters vector |
| summary-method | Symmetric matrix object: Random parameters symmetric matrix |
| summary-method | Distribution Objects |
| summary-method | Class '"VirtualRSet"', '"SimLabels"' and '"SimRSet"' |
| summaryFit | Provide summary of model fit across replications |
| summaryFit-method | Provide summary of model fit across replications |
| summaryFit-methods | Provide summary of model fit across replications |
| summaryMisspec | Provide summary of model misspecification imposed across replications |
| summaryMisspec-method | Provide summary of model misspecification imposed across replications |
| summaryMisspec-methods | Provide summary of model misspecification imposed across replications |
| summaryParam | Provide summary of parameter estimates and standard error across replications |
| summaryParam-method | Class '"SimResultParam"' |
| summaryParam-method | Provide summary of parameter estimates and standard error across replications |
| summaryParam-methods | Provide summary of parameter estimates and standard error across replications |
| summaryPopulation | Summarize the data generation population model underlying an object |
| summaryPopulation-method | Class '"SimDataOut"' |
| summaryPopulation-method | Class '"SimModelOut"' |
| summaryPopulation-method | Class '"SimResult"' |
| summaryPopulation-method | Summarize the data generation population model underlying an object |
| summaryPopulation-methods | Summarize the data generation population model underlying an object |
| summaryShort | Provide short summary of an object. |
| summaryShort-method | Matrix object: Random parameters matrix |
| summaryShort-method | Vector object: Random parameters vector |
| summaryShort-method | Distribution Objects |
| summaryShort-method | Provide short summary of an object. |
| summaryShort-methods | Provide short summary of an object. |
| symMatrix | Create symmetric simMatrix that save free parameters and starting values, as well as fixed values |
| SymMatrix-class | Symmetric matrix object: Random parameters symmetric matrix |
| tagHeaders | Tag names to each element |
| tagHeaders-method | Tag names to each element |
| tagHeaders-methods | Tag names to each element |
| toFunction | Export the distribution object to a function command in text that can be evaluated directly. |
| toFunction-method | Distribution Objects |
| toFunction-method | Export the distribution object to a function command in text that can be evaluated directly. |
| toFunction-methods | Export the distribution object to a function command in text that can be evaluated directly. |
| toSimSet | Transform the analysis model object into the object for data generation |
| toSimSet-method | Transform the analysis model object into the object for data generation |
| toSimSet-methods | Transform the analysis model object into the object for data generation |
| twoTailedPValue | Find two-tailed _p_ value from one-tailed _p_ value |
| validateCovariance | Validate whether all elements provides a good covariance matrix |
| validateObject | Validate whether the drawn parameters are good. |
| validatePath | Validate whether the regression coefficient (or loading) matrix is good |
| vectorizeObject | Change an object to a vector with labels |
| vectorizeObject-method | Change an object to a vector with labels |
| vectorizeObject-methods | Change an object to a vector with labels |
| VirtualDist-class | Distribution Objects |
| VirtualRSet-class | Class '"VirtualRSet"', '"SimLabels"' and '"SimRSet"' |
| weightedMean | Calculate the weighted mean of a variable |
| whichMonotonic | Extract a part of a vector that is monotonically increasing or decreasing |
| writeLavaanCode | Write a lavaan code given the matrices of free parameter |
| writeLavaanConstraint | Write a lavaan code for a given set of equality constraints |
| writeLavaanIndividualConstraint | Write a lavaan code for a given equality constraint for each parameter |
| writeLavaanNullCode | Write a lavaan code for a null model |