Mplus Users Guide v6.. - Muthén & Muthén

CHAPTER 18where b is the unstandardized linear regression coefficient, SD(x) is thesample standard deviation of x, and SD(y) is the model estimatedstandard deviation of y. The standardized coefficient b StdYX isinterpreted as the change in y in y standard deviation units for a standarddeviation change in x.The second type of standardization is shown under the heading StdY inthe output. StdY uses the variances of the continuous latent variables aswell as the variances of the outcome variables for standardization. TheStdY standardization for the linear regression of y on x isb StdY = b/SD(y).StdY should be used for binary covariates because a standard deviationchange of a binary variable is not meaningful. The standardizedcoefficient b StdY is interpreted as the change in y in y standard deviationunits when x changes from zero to one.The third type of standardization is shown under the heading Std in theoutput. Std uses the variances of the continuous latent variables forstandardization.Covariances are standardized using variances. Residual covariances arestandardized using residual variances. This is the case for both latentand observed variables.Options are available to request one or two of the standardizations.They are STANDARDIZED (STDYX), STANDARDIZED (STDY), andSTANDARDIZED (STD). To request only the standardization that usesthe variances of the continuous latent variables as well as the variancesof the background and outcome variables, specify:STANDARDIZED (STDYX);To request both the standardization that uses the variances of thecontinuous latent variables as well as the variances of the backgroundand outcome variables and the standardization that uses the variances ofthe continuous latent variables and the variances of the outcomevariables, specify:STANDARDIZED (STDYX STDY);642