standardized_estimates.modsem_da

Get standardized estimates with Monte Carlo bootstrapped standard errors

Estimation of interaction (i.e., moderation) effects between latent variables
in structural equation models (SEM).
The supported methods are:
The constrained approach (Algina & Moulder, 2001).
The unconstrained approach (Marsh et al., 2004).
The residual centering approach (Little et al., 2006).
The double centering approach (Lin et al., 2010).
The latent moderated structural equations (LMS) approach (Klein & Moosbrugger, 2000).
The quasi-maximum likelihood (QML) approach (Klein & Muthén, 2007) (temporarily unavailable)
The constrained- unconstrained, residual- and double centering- approaches
are estimated via 'lavaan' (Rosseel, 2012), whilst the LMS- and QML- approaches
are estimated via 'modsem' it self. Alternatively model can be
estimated via 'Mplus' (Muthén & Muthén, 1998-2017).
References:
Algina, J., & Moulder, B. C. (2001).
<doi:10.1207/S15328007SEM0801_3>.
"A note on estimating the Jöreskog-Yang model for latent variable interaction using 'LISREL' 8.3."
Klein, A., & Moosbrugger, H. (2000).
<doi:10.1007/BF02296338>.
"Maximum likelihood estimation of latent interaction effects with the LMS method."
Klein, A. G., & Muthén, B. O. (2007).
<doi:10.1080/00273170701710205>.
"Quasi-maximum likelihood estimation of structural equation models with multiple interaction and quadratic effects."
Lin, G. C., Wen, Z., Marsh, H. W., & Lin, H. S. (2010).
<doi:10.1080/10705511.2010.488999>.
"Structural equation models of latent interactions: Clarification of orthogonalizing and double-mean-centering strategies."
Little, T. D., Bovaird, J. A., & Widaman, K. F. (2006).
<doi:10.1207/s15328007sem1304_1>.
"On the merits of orthogonalizing powered and product terms: Implications for modeling interactions among latent variables."
Marsh, H. W., Wen, Z., & Hau, K. T. (2004).
<doi:10.1037/1082-989X.9.3.275>.
"Structural equation models of latent interactions: evaluation of alternative estimation strategies and indicator construction."
Muthén, L.K. and Muthén, B.O. (1998-2017).
"'Mplus' User’s Guide. Eighth Edition."
<https://www.statmodel.com/>.
Rosseel Y (2012).
<doi:10.18637/jss.v048.i02>.
"'lavaan': An R Package for Structural Equation Modeling."

Kjell Solem Slupphaug

modsem

Latent Interaction (and Moderation) Analysis in Structural
Equation Models (SEM)

Mehmet Mehmetoglu

Matthias Mittner

standardized_estimates.modsem_da function

<dl><dt>object</dt>
<dd>An object of class <code>modsem_da</code></dd>
<dt>monte.carlo</dt>
<dd>Should standard errors be calculated using Monte Carlo simulation. 
if <code>FALSE</code> the delta method is used instead. Default is <code>FALSE</code>.</dd>
<dt>mc.reps</dt>
<dd>Number of Monte Carlo repetitions</dd>
<dt>tolerance.zero</dt>
<dd>Tolerance for zero values. Standard errors smaller than this 
value will be set to NA.</dd>
<dt>...</dt>
<dd>Additional arguments passed to other functions</dd></dl>

Arguments

Get standardized estimates with Monte Carlo bootstrapped standard errors — standardized_estimates.modsem_da

<dl>

<dt>object</dt>
<dd>An object of class <code>modsem_da</code></dd>


<dt>monte.carlo</dt>
<dd>Should standard errors be calculated using Monte Carlo simulation. 
if <code>FALSE</code> the delta method is used instead. Default is <code>FALSE</code>.</dd>


<dt>mc.reps</dt>
<dd>Number of Monte Carlo repetitions</dd>


<dt>tolerance.zero</dt>
<dd>Tolerance for zero values. Standard errors smaller than this 
value will be set to NA.</dd>


<dt>...</dt>
<dd>Additional arguments passed to other functions</dd>

</dl>

standardized_estimates.modsem_da: Get standardized estimates with Monte Carlo bootstrapped standard errors

Description

Usage

Arguments

Details