Extract all possible paths from one variable to another connected component in a latent variable model. In an estimated model the effect size is decomposed into direct, indirect and total effects including approximate standard errors.
# S3 method for lvm path (object, to = NULL, from, all=FALSE, ...) # S3 method for lvmfit effects (object, to, from, ...)
Model object (
Additional arguments to be passed to the low level functions
Outcome variable (string). Alternatively a formula specifying
response and predictor in which case the argument
Response variable (string), not necessarily directly affected by
If TRUE all simple paths (in undirected graph) is returned on/off.
object is of class
lvmfit a list with the following
elements is returned
A list where each element defines a possible pathway via a integer vector indicating the index of the visited nodes.
A List of covariance matrices for each path.
A list of parameters estimates for each path
A list where each element defines a possible pathway via a character vector naming the visited nodes in order.
Description of 'comp2'
lvmfit-object the parameters estimates and their
corresponding covariance matrix are also returned. The
effects-function additionally calculates the total and indirect
effects with approximate standard errors
Klaus K. Holst
m <- lvm(c(y1,y2,y3)~eta) regression(m) <- y2~x1 latent(m) <- ~eta regression(m) <- eta~x1+x2 d <- sim(m,500) e <- estimate(m,d) path(Model(e),y2~x1)#> [] #>  "x1" "y2" #> #> [] #>  "x1" "eta" "y2" #>#>  "eta" "x1"#>  "eta"#>  "eta" "y1" "y2" "y3"effects(e,y2~x1)#> Estimate Std.Err z value Pr(>|z|) #> Total 2.0041 0.06400 31.31 3.111e-215 #> Direct 0.9491 0.07118 13.33 1.460e-40 #> Indirect 1.0549 0.07285 14.48 1.599e-47 #> y2~eta~x1 1.0549 0.07285 14.48 1.599e-47 #> #> Estimate 2.5% 97.5% #> Mediation proportion 0.5264 0.4633 0.5895## All simple paths (undirected) path(m,y1~x1,all=TRUE)#> [] #>  "x1" "y2" "eta" "y1" #> #> [] #>  "x1" "eta" "y1" #>