ramLCS: Univariate latent change score model

In RAMpath: Structural Equation Modeling Using the Reticular Action Model (RAM) Notation

Univariate latent change score model

Description

Univariate latent change score model

Usage

ramLCS(data, y, timey, ram.out = FALSE, betay, my0, mys, 
varey, vary0, varys, vary0ys, ...)

Arguments

data	data
y	y data
timey	time of y
ram.out	Whether print ram matrices
betay	Starting value
my0	Starting value
mys	Starting value
varey	Starting value
vary0	Starting value
varys	Starting value
vary0ys	Starting value
...	Options can be used for lavaan

Value

model	The lavaan model specification of the bivariate latent change score model
lavaan	The lavaan output
ram	Output in terms of RAM matrices

References

Zhang, Z., Hamagami, F., Grimm, K. J., & McArdle, J. J. (2015). Using R package RAMpath for tracing SEM path diagrams and conducting complex longitudinal data analysis. Structural Equation Modeling, 22(1), 132-147. https://doi.org/10.1080/10705511.2014.935257

Examples

data(ex3)
test.lcs<-ramLCS(ex3, 7:12)
summary(test.lcs$lavaan, fit=TRUE)

bridge<-ramPathBridge(test.lcs$ram, allbridge=FALSE, indirect=FALSE)
## uncomment to plot
## plot(bridge, 'lcs')

RAMpath documentation built on Aug. 27, 2023, 5:06 p.m.