The purpose of this investigation is to compare a new (double-mean-centering) strategy to estimating latent interactions in structural equation models with the (single) mean-centering strategy (Marsh, Wen, & Hau, 2004, 2006) and the orthogonalizing strategy (Little, Bovaird, & Widaman, 2006; Marsh et al., 2007). A key benefit of the orthogonalizing strategy is that it eliminated the need to estimate a mean structure as required by the mean-centering strategy, but required a potentially cumbersome 2-step estimation procedure. In contrast, the double-mean-centering strategy eliminates both the need for the mean structure and the cumbersome 2-stage estimation procedure. Furthermore, although the orthogonalizing and double-mean-centering strate...
The current study aimed to determine the best method for estimating latent variable interactions as ...
The cross-product term in moderated regression may be collinear with its constituent parts, making i...
Mean centering is an additive transformation of a continuous variable. It is often used in moderated...
Little, Bovaird and Widaman (2006) proposed an unconstrained approach with residual centering for es...
Estimation methods for structural equation models with interactions of latent variables were compare...
Interactions between (multiple indicator) latent variables are rarely used because of implementation...
Abstract. Structural equation models with mean structure and non-linear constraints are the most fre...
Standardized parameter estimates are routinely used to summarize the results of multiple regression ...
Standardized parameter estimates are routinely used to summarize the results of multiple regression ...
This Monte Carlo simulation study investigated different strategies for forming product indicators f...
This Monte Carlo simulation study investigated different strategies for forming product indicators f...
In social and business sciences, the importance of the analysis of interaction effects between manif...
In hierarchical data, the effect of a lower-level predictor on a lower-level outcome may often be co...
Covariance Based – Structural Equation Modelling (CB-SEM) is often used to investigate moderation an...
In social and business sciences, the importance of the analysis of interaction effects between manif...
The current study aimed to determine the best method for estimating latent variable interactions as ...
The cross-product term in moderated regression may be collinear with its constituent parts, making i...
Mean centering is an additive transformation of a continuous variable. It is often used in moderated...
Little, Bovaird and Widaman (2006) proposed an unconstrained approach with residual centering for es...
Estimation methods for structural equation models with interactions of latent variables were compare...
Interactions between (multiple indicator) latent variables are rarely used because of implementation...
Abstract. Structural equation models with mean structure and non-linear constraints are the most fre...
Standardized parameter estimates are routinely used to summarize the results of multiple regression ...
Standardized parameter estimates are routinely used to summarize the results of multiple regression ...
This Monte Carlo simulation study investigated different strategies for forming product indicators f...
This Monte Carlo simulation study investigated different strategies for forming product indicators f...
In social and business sciences, the importance of the analysis of interaction effects between manif...
In hierarchical data, the effect of a lower-level predictor on a lower-level outcome may often be co...
Covariance Based – Structural Equation Modelling (CB-SEM) is often used to investigate moderation an...
In social and business sciences, the importance of the analysis of interaction effects between manif...
The current study aimed to determine the best method for estimating latent variable interactions as ...
The cross-product term in moderated regression may be collinear with its constituent parts, making i...
Mean centering is an additive transformation of a continuous variable. It is often used in moderated...