R: Residual-center all target indicators by covariates

residualCovariate {semTools} | R Documentation

## Residual-center all target indicators by covariates

### Description

This function will regress target variables on the covariate and replace the target variables by the residual of the regression analysis. This procedure is useful to control the covariate from the analysis model (Geldhof, Pornprasertmanit, Schoemann, & Little, 2013).

### Usage

    residualCovariate(data, targetVar, covVar)

### Arguments

`data` | The desired data to be transformed.
`targetVar` | Varible names or the position of indicators that users wish to be residual centered (as dependent variables)
`covVar` | Covariate names or the position of the covariates using for residual centering (as independent variables) onto target variables

### Value

The data that the target variables replaced by the residuals

### Author(s)

Sunthud Pornprasertmanit (psunthud@gmail.com)

### References

Geldhof, G. J., Pornprasertmanit, S., Schoemann, A. M., & Little, T. D. (2013). Orthogonalizing through residual centering: Extended applications and caveats. Educational and Psychological Measurement, 73(1), 27–46. doi:10.1177/0013164412445473

### See Also

`indProd` For creating the indicator products with no centering, mean centering, double-mean centering, or residual centering.

### Examples

    dat <- residualCovariate(attitude, 2:7, 1)

[Package semTools version 0.5-1 Index]