Model searching
Performs Wald or score tests
modelsearch(x, k = 1, dir = "forward", type = "all", ...)
x |
|
k |
Number of parameters to test simultaneously. For |
dir |
Direction to do model search. "forward" := add associations/arrows to model/graph (score tests), "backward" := remove associations/arrows from model/graph (wald test) |
type |
If equal to 'correlation' only consider score tests for covariance parameters. If equal to 'regression' go through direct effects only (default 'all' is to do both) |
... |
Additional arguments to be passed to the low level functions |
Matrix of test-statistics and p-values
Klaus K. Holst
m <- lvm(); regression(m) <- c(y1,y2,y3) ~ eta; latent(m) <- ~eta regression(m) <- eta ~ x m0 <- m; regression(m0) <- y2 ~ x dd <- sim(m0,100)[,manifest(m0)] e <- estimate(m,dd); modelsearch(e,messages=0) modelsearch(e,messages=0,type="cor")
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