indProd: Make a product of indicators using mean centering or double-mean centering

Description

This function will use mean centering or double is a constrctor of a function object which can be used for data transformation. The aim of the object is to create a function but will use later in a simulation study. For example, set up a mean centering for a dataset for using in a simulation.

Usage

indProd(data, var1, var2, match = TRUE, meanC = TRUE, residualC = FALSE, doubleMC = TRUE, namesProd = NULL)

Arguments

data

The desired data to be transformed.

var1

Names or indices of the variables loaded on the first factor

var2

Names or indices of the variables loaded on the second factor

match

Specify TRUE to use match-paired approach (Marsh, Wen, & Hau, 2004). If FALSE, the resulting products are all possible products.

meanC

Specify TRUE for mean centering the main effect indicator before making the products

residualC

Specify TRUE for residual centering the products by the main effect indicators (Little, Bovaird, & Widaman, 2006).

doubleMC

Specify TRUE for centering the resulting products (Lin et. al., 2010)

namesProd

The names of resulting products

Value

The original data attached with the products.

References

Marsh, H. W., Wen, Z. & Hau, K. T. (2004). Structural equation models of latent interactions: Evaluation of alternative estimation strategies and indicator construction.Psychological Methods, 9,275-300.
Lin, G. C., Wen, Z., Marsh, H. W., & Lin, H. S. (2010). Structural equation models of latent interactions: Clarification of orthogonalizing and double-mean-centering strategies.Structural Equation Modeling, 17, 374-391.
Little, T. D., Bovaird, J. A., & Widaman, K. F. (2006). On the merits of orthogonalizing powered and product terms: Implications for modeling interactions among latent variables.Structural Equation Modeling, 13, 497-519.

Examples

Run this code

dat <- indProd(attitude[,-1], var1=1:3, var2=4:6)