Learn R Programming

symSEM (version 0.1)

impliedS: Compute a Symbolic Model-Implied Covariance/Correlation Matrix

Description

It computes a symbolic model-implied covariance (or correlation) matrix in SEM using the RAM inputs.

Usage

impliedS(RAM, corr=FALSE)

Value

The model implied covariance (or correlation) matrix.

Arguments

RAM

A RAM object including a list of matrices of the model returned from lavaan2RAM

corr

Whether the model implied matrix is covariance (default) or correlation.

Author

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

Examples

Run this code
#### A mediation model
model1 <- "y ~ c*x + b*m
           m ~ a*x
           ## Means
           y ~ b0*1
           m ~ m0*1
           x ~ x0*1"
    
RAM1 <- metaSEM::lavaan2RAM(model1)

## Model-implied covariance matrix and mean structure
impliedS(RAM1, corr=FALSE)

## Model-implied correlation matrix
impliedS(RAM1, corr=TRUE)

#### A CFA model
model2 <- "f =~ x1 + x2 + x3 + x4"
    
RAM2 <- metaSEM::lavaan2RAM(model2)

## Model-implied covariance matrix
impliedS(RAM2, corr=FALSE)

## Model-implied correlation matrix
impliedS(RAM2, corr=TRUE)

Run the code above in your browser using DataLab