plotSEMM-package {plotSEMM} | R Documentation |
Contains functions plotSEMM_setup
, plotSEMM_contour
, plotSEMM_probability
and plotSEMM_legend
. Creates plots which accompany Bauers (2005) semiparametric method of modeling Structural Equation Mixture Models (SEMMs) by allowing researchers to visualize potential nonlinear relationships between a latent predictor and outcome.
Package: | plotSEMM |
Type: | Package |
Version: | 1.0 |
Date: | 2008-03-11 |
License: | GPL (>= 2) |
Contains four functions:
plotSEMM_setup
takes and organizes user input generated from SEMM software such as Mplus (Muthen & Muthen, 2007), Mx (Neale, Boker, Xie & Maes, 2004) or MECOSA (Arminger, Wittenberg, & Schepers, 1996) in Gauss. The user needs to specify 6 vectors of model estimates, each containing K elements where K is the number of classes estimated. These vectors are specified to include (1) the marginal class probabilities, pi
(2) the class means for the latent predictor, alpha1
; (3) the intercepts and (4) slopes from the within-class regression of the latent outcome on the latent predictor, alpha2
and beta21
; (5) the within class variances of the latent predictor, psi11
; and (6) the within-class residual variances of the latent outcome, psi22
.
plotSEMM_contour
generates (a) the potential nonlinear regression function; (b) bivariate distribution of the latent variables; (c) marginal distributions of the latent variables; (d) within class linear regression functions; and (e) within class marginal distributions for the latent variables.
plotSEMM_probability
generates a plot which expresses the mixing probabilities for each latent class conditioned on the exogenous latent variable, working from the data structure provided by plotSEMM_setup
.
plotSEMM_legend
generates an optional legend to accompany the above plots.
Bethany E. Kok, Jolynn Pek, Sonya Sterba and Dan Bauer
Maintainer: Bethany E. Kok bethanyk@unc.edu
Bauer, D.J. (2005). A semiparametric approach to modeling nonlinear relations among latent variables. Structural Equation Modeling: A Multidisciplinary Journal, 12(4), 513-535.
Pek, J., Sterba, S., Kok, B.E. & Bauer, D.J. (in prep). Visualizing nonlinear relations among latent variables: An online plotting utility and R package.
http://www.bethanykok.com/plotSEMM.html