# Estimate the asymptotic covariance matrix of standardized or unstandardized indirect and direct effects

### Description

It estimates the standardized or unstandardized indirect and direct effects and their asymptotic sampling covariance matrix.

### Usage

1 | ```
indirectEffect(x, n, standardized = TRUE, direct.effect = TRUE, run = TRUE)
``` |

### Arguments

`x` |
A 3x3 correlation/covariance matrix or a list of correlation/covariance matrices. Variables are arranged as dependent variable (y), mediator (m) and independent variable (x) |

`n` |
Sample size or a vector of sample sizes |

`standardized` |
Logical. Whether the indirect effect is standardized. |

`direct.effect` |
Logical. Whether the direct effect is
estimated. If it is |

`run` |
Logical. If |

### Details

Cheung (2009) estimated the standardized indirect effect and
its standard error with non-linear constraints. Since `OpenMx`

does not generate standard errors when there
are non-linear constraints, Kwan and Chan's (2011) approach is used in
this function. Delta method is used to calculate the asymptotic covariance matrix.

### Value

A vector (or a matrix if the input is a list of matrices) of (standardized) indirect effect, standardized direct effect and their asymptotic sampling covariance matrices

### Author(s)

Mike W.-L. Cheung <mikewlcheung@nus.edu.sg>

### References

Cheung, M. W.-L. (2009). Comparison of methods for constructing confidence intervals of standardized indirect effects. *Behavior
Research Methods*, *41*, 425-438.

Kwan, J., & Chan, W. (2011). Comparing standardized coefficients in
structural equation modeling: a model reparameterization
approach. *Behavior Research Methods*, *43*, 730-745.

### Examples

1 2 3 4 5 6 7 |

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