Nothing
knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
library(lcsm)
This function is work in progress and can only plot univariate and bivariate LCSMs that were specified with fit_uni_lcsm()
or fit_bi_lcsm()
.
Modified LCSMs will probably return errors as the layout matrix that gets created by this plot function only supports the specifications that can be modelled with this package.
The input arguments for plotting a simplified path dioagram are:
lavaan_object
,lavaan_syntax
and ,lcsm
indicating whether the LCSM is "univariate" or "bivariate"Optional arguments can be used to change the look of the plot, for example:
lcsm_colours
can be used to highlight the different parts of the latent change score modelFurther arguments can be passed on to semPlot::semPaths()
, for example:
what
, "path" to show unweighted gray edges, "par" to show parameter estimates as weighted (green/red) edges whatLabels
, "label" to show edege names as label or "est" for parameter estimates, "hide" to hide edge labels# Fit bivariate lcsm and save the results uni_lavaan_results <- fit_uni_lcsm(data = data_uni_lcsm, var = c("x1", "x2", "x3", "x4", "x5"), model = list(alpha_constant = TRUE, beta = FALSE, phi = TRUE) ) # Save the lavaan syntax that is used to create the layout matrix for semPlot uni_lavaan_syntax <- fit_uni_lcsm(data = data_uni_lcsm, var = c("x1", "x2", "x3", "x4", "x5"), model = list(alpha_constant = TRUE, beta = FALSE, phi = TRUE), return_lavaan_syntax = TRUE) # Plot the results plot_lcsm(lavaan_object = uni_lavaan_results, lavaan_syntax = uni_lavaan_syntax, edge.label.cex = .9, lcsm_colours = TRUE, lcsm = "univariate")
# Fit bivariate lcsm and save the results bi_lavaan_results <- fit_bi_lcsm(data = data_bi_lcsm, var_x = c("x1", "x2", "x3", "x4", "x5"), var_y = c("y1", "y2", "y3", "y4", "y5"), model_x = list(alpha_constant = TRUE, beta = TRUE, phi = FALSE), model_y = list(alpha_constant = TRUE, beta = TRUE, phi = TRUE), coupling = list(delta_lag_xy = TRUE, xi_lag_yx = TRUE)) # Save the lavaan syntax that is used to create the layout matrix for semPlot bi_lavaan_syntax <- fit_bi_lcsm(data = data_bi_lcsm, var_x = c("x1", "x2", "x3", "x4", "x5"), var_y = c("y1", "y2", "y3", "y4", "y5"), model_x = list(alpha_constant = TRUE, beta = TRUE, phi = FALSE), model_y = list(alpha_constant = TRUE, beta = TRUE, phi = TRUE), coupling = list(delta_lag_xy = TRUE, xi_lag_yx = TRUE), return_lavaan_syntax = TRUE) # Plot the results plot_lcsm(lavaan_object = bi_lavaan_results, lavaan_syntax = bi_lavaan_syntax, lcsm_colours = TRUE, whatLabels = "hide", lcsm = "bivariate")
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