Compute a variety of test statistics evaluating the global fit of the model.
lavTest(lavobject, test = "standard", scaled.test = "standard",
output = "list", drop.list.single = TRUE)
If output = "list"
: a nested list with test statistics, or if
only a single test statistic is requested (and
drop.list.single = TRUE
), a list with details for this test
statistic. If output = "text"
: the text is printed, and a
nested list of test statistics (including an info attribute) is
returned.
An object of class lavaan
.
Character vector. Multiple names of test statistics can be provided.
If "standard"
is included, a conventional chi-square test
is computed. If "Browne.residual.adf"
is included,
Browne's residual-based test statistic using ADF theory is computed.
If "Browne.residual.nt"
is included, Browne's residual-based
test statistic using normal theory is computed.
If "Satorra.Bentler"
is included, a Satorra-Bentler scaled test
statistic is computed. If "Yuan.Bentler"
is included,
a Yuan-Bentler scaled test statistic is computed.
If "Yuan.Bentler.Mplus"
is included, a
test statistic is computed that is asymptotically equal to the
Yuan-Bentler scaled test statistic. If "mean.var.adjusted"
or
"Satterthwaite"
is included, a mean and variance adjusted test
statistic is computed. If "scaled.shifted"
is included,
an alternative mean and variance adjusted test statistic is
computed (as in Mplus version 6 or higher).
If "boot"
or "bootstrap"
or "Bollen.Stine"
is
included, the
Bollen-Stine bootstrap is used to compute the bootstrap probability value
of the (regular) test statistic.
Character. Choose the test statistic
that will be scaled (if a scaled test statistic is requested).
The default is "standard"
, but it could also be (for example)
"Browne.residual.nt"
.
Character. If "list"
(the default), return a list with
all test statistics. If "text"
, display the output as text with
verbose descriptions (as in the summary output). If any scaled
test statistics are included, they are printed first in a two-column
format. Next come the other test statistics in a one-column format.
Logical. Only used when output = "list"
.
If TRUE
and the list is of length one (i.e. only a single test
statistic), drop the outer list. If FALSE
, return a nested list
with as many elements as we have test statistics.
HS.model <- '
visual =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed =~ x7 + x8 + x9
'
fit <- cfa(HS.model, data = HolzingerSwineford1939)
lavTest(fit, test = "browne.residual.adf")
Run the code above in your browser using DataLab