LMS {powerNLSEM} | R Documentation |
Latent moderated strctured equations by Klein and Moosbrugger (2000), the ML approach to nonlinear SEM
Description
Latent moderated strctured equations by Klein and Moosbrugger (2000), the ML approach to nonlinear SEM
Usage
LMS(
lavModel_Analysis,
data,
data_transformations = NULL,
prefix = 1,
pathLMS = tempdir(),
algorithm = "INTEGRATION"
)
Arguments
lavModel_Analysis |
the lavModel_Analysis object |
data |
set to fit |
data_transformations |
Object containing info on possible data transformations. |
prefix |
an arbitrary prefix for the data set. This prevents issues when using parallelization and Mplus. |
pathLMS |
path where (temporal) data and scripts for running LMS using Mplus are stored (using |
algorithm |
algorithm to use. Default to INTEGRATION. |
Value
Returns a data.frame
that includes parameter estimates estimated using LMS.
References
Klein, A. G., & Moosbrugger, H. (2000). Maximum likelihood estimation of latent interaction effects with the LMS method. Psychometrika, 65(4), 457–474. doi:10.1007/BF02296338
[Package powerNLSEM version 0.1.1 Index]