Extract pathways in model graph
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 class 'lvm' path(object, to = NULL, from, all=FALSE, ...) ## S3 method for class 'lvmfit' effects(object, to, from, ...)
object |
Model object ( |
... |
Additional arguments to be passed to the low level functions |
to |
Outcome variable (string). Alternatively a formula specifying
response and predictor in which case the argument |
from |
Response variable (string), not necessarily directly affected by
|
all |
If TRUE all simple paths (in undirected graph) is returned on/off. |
If object is of class lvmfit a list with the following
elements is returned
idx |
A list where each element defines a possible pathway via a integer vector indicating the index of the visited nodes. |
V |
A List of covariance matrices for each path. |
coef |
A list of parameters estimates for each path |
path |
A list where each element defines a possible pathway via a character vector naming the visited nodes in order. |
edges |
Description of 'comp2' |
If object is of class lvm only the path element will be
returned.
The effects method returns an object of class effects.
For a 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
children, parents
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) parents(Model(e), ~y2) children(Model(e), ~x2) children(Model(e), ~x2+eta) effects(e,y2~x1) ## All simple paths (undirected) path(m,y1~x1,all=TRUE)
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