lavTestLRT | R Documentation |
LRT test for comparing (nested) lavaan models.
lavTestLRT(object, ..., method = "default", A.method = "delta",
scaled.shifted = TRUE,
H1 = TRUE, type = "Chisq", model.names = NULL)
anova(object, ...)
object |
An object of class |
... |
additional objects of class |
method |
Character string. The possible options are
|
H1 |
Not used yet |
A.method |
Character string. The possible options are |
scaled.shifted |
Logical. Only used when method = |
type |
Character. If |
model.names |
Character vector. If provided, use these model names in the first column of the anova table. |
The anova
function for lavaan objects simply calls the
lavTestLRT
function, which has a few additional arguments.
If type = "Chisq"
and the test statistics are scaled, a
special scaled difference test statistic is computed. If method is
"satorra.bentler.2001"
, a simple approximation is used
described in Satorra & Bentler (2001). In some settings,
this can lead to a negative test statistic. To ensure a positive
test statistic, we can use the method proposed by
Satorra & Bentler (2010). Alternatively, when method is
"satorra.2000"
, the original formulas of Satorra (2000) are
used.
An object of class anova. When given a single argument, it simply returns the test statistic of this model. When given a sequence of objects, this function tests the models against one another, after reordering the models according to their degrees of freedom.
Satorra, A. (2000). Scaled and adjusted restricted tests in multi-sample analysis of moment structures. In Heijmans, R.D.H., Pollock, D.S.G. & Satorra, A. (eds.), Innovations in multivariate statistical analysis. A Festschrift for Heinz Neudecker (pp.233-247). London: Kluwer Academic Publishers.
Satorra, A., & Bentler, P. M. (2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66(4), 507-514.
Satorra, A., & Bentler, P. M. (2010). Ensuring postiveness of the scaled difference chi-square test statistic. Psychometrika, 75(2), 243-248.
HS.model <- '
visual =~ x1 + b1*x2 + x3
textual =~ x4 + b2*x5 + x6
speed =~ x7 + b3*x8 + x9
'
fit1 <- cfa(HS.model, data = HolzingerSwineford1939)
fit0 <- cfa(HS.model, data = HolzingerSwineford1939,
orthogonal = TRUE)
lavTestLRT(fit1, fit0)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.