The lavaan
class represents a (fitted) latent variable
model. It contains a description of the model as specified by the user,
a summary of the data, an internal matrix representation, and if the model
was fitted, the fitting results.
version
:The lavaan package version used to create this objects.
call
:The function call as returned by match.call()
.
timing
:The elapsed time (user+system) for various parts of the program as a list, including the total time.
Options
:Named list of options that were provided by the user, or filled-in automatically.
ParTable
:Named list describing the model parameters. Can be coerced to a data.frame. In the documentation, this is called the `parameter table'.
pta
:Named list containing parameter table attributes.
Data
:Object of internal class "Data"
: information
about the data.
SampleStats
:Object of internal class "SampleStats"
: sample
statistics
Model
:Object of internal class "Model"
: the
internal (matrix) representation of the model
Cache
:List using objects that we try to compute only once, and reuse many times.
Fit
:Object of internal class "Fit"
: the
results of fitting the model
boot
:List. Results and information about the bootstrap.
optim
:List. Information about the optimization.
loglik
:List. Information about the loglikelihood of the model (if maximum likelihood was used).
implied
:List. Model implied statistics.
vcov
:List. Information about the variance matrix (vcov) of the model parameters.
test
:List. Different test statistics.
h1
:List. Information about the unrestricted h1 model (if available).
baseline
:List. Information about a baseline model (often the independence model) (if available).
external
:List. Empty slot to be used by add-on packages.
signature(object = "lavaan", type = "free")
: Returns
the estimates of the parameters in the model as a named numeric vector.
If type="free"
, only the free parameters are returned.
If type="user"
, all parameters listed in the parameter table
are returned, including constrained and fixed parameters.
signature(object = "lavaan")
: Returns the
implied moments of the model as a list with two elements (per group):
cov
for the implied covariance matrix,
and mean
for the implied mean
vector. If only the covariance matrix was analyzed, the implied mean
vector will be zero.
signature(object = "lavaan")
: an alias for
fitted.values
.
signature(object = "lavaan", type="raw")
:
If type="raw"
, this function returns the raw (=unstandardized)
difference between the implied moments and the observed moments as
a list of two elements: cov
for the residual covariance matrix,
and mean
for the residual mean vector.
If only the covariance matrix was analyzed, the residual mean vector
will be zero.
If type="cor"
, the observed and model implied covariance matrix
is first transformed to a correlation matrix (using cov2cor
),
before the residuals are computed.
If type="normalized"
, the residuals are
divided by the square root of an asymptotic variance estimate of the
corresponding sample statistic (the variance estimate depends on the
choice for the se
argument).
If type="standardized"
, the residuals are divided by the square
root of the difference between an asymptotic variance estimate of the
corresponding sample statistic and an asymptotic variance estimate of
the corresponding model-implied statistic.
In the latter case, the residuals have a metric similar
to z-values. On the other hand, they may often result in NA
values; for these cases, it may be better to use the normalized residuals. For
more information about the normalized and standardized residuals, see
the Mplus reference below.
signature(object = "lavaan")
: an alias
for residuals
signature(object = "lavaan")
: returns the
covariance matrix of the estimated parameters.
signature(object = "lavaan")
: compute
factor scores for all cases that are provided in the data frame. For
complete data only.
signature(object = "lavaan")
: returns
model comparison statistics. This method is just a wrapper around
the function lavTestLRT
.
If only a single argument (a fitted
model) is provided, this model is compared to the unrestricted
model. If two or more arguments (fitted models) are provided, the models
are compared in a sequential order. Test statistics are based on the
likelihood ratio test. For more details and
further options, see the lavTestLRT
page.
signature(object = "lavaan", model, add, ...,
evaluate=TRUE)
: update a fitted lavaan object and evaluate it
(unless evaluate=FALSE
). Note that we use the environment
that is stored within the lavaan object, which is not necessarily
the parent frame. The add
argument is analogous to the one
described in the lavTestScore
page, and can be used to
add parameters to the specified model rather than passing an entirely
new model
argument.
signature(object = "lavaan")
: returns the effective
number of observations used when fitting the model. In a multiple group
analysis, this is the sum of all observations per group.
signature(object = "lavaan")
:
returns the log-likelihood of the fitted model, if maximum likelihood estimation
was used. The AIC
and BIC
methods automatically work via logLik()
.
signature(object = "lavaan")
: Print a short summary
of the model fit
signature(object = "lavaan", header = TRUE, fit.measures=FALSE, estimates = TRUE, ci = FALSE, fmi = FALSE, standardized = FALSE,
cov.std = TRUE, rsquare=FALSE, std.nox = FALSE, modindices=FALSE, ci=FALSE, nd = 3L)
:
Print a nice summary of the model estimates.
If header = TRUE
, the header section (including fit measures) is
printed.
If fit.measures = TRUE
, additional fit measures are added to the
header section.
If estimates = TRUE
, print the parameter estimates section.
If ci = TRUE
, add confidence intervals to the parameter estimates
section.
If fmi = TRUE
, add the fmi (fraction of missing information)
column, if it is available.
If standardized=TRUE
,
the standardized solution is also printed.
If rsquare=TRUE
, the R-Square values for the dependent variables
in the model are printed.
If std.nox = TRUE
, the std.all
column contains the
the std.nox
column from the parameterEstimates() output.
If modindices=TRUE
, modification indices
are printed for all fixed parameters.
The argument nd
determines the number of digits after the
decimal point to be printed (currently only in the parameter estimates
section.)
Nothing is returned (use
lavInspect
or another extractor function
to extract information from a fitted model).
Yves Rosseel (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. URL http://www.jstatsoft.org/v48/i02/.
Standardized Residuals in Mplus. Document retrieved from URL http://www.statmodel.com/download/StandardizedResiduals.pdf
cfa
, sem
, growth
,
fitMeasures
, standardizedSolution
,
parameterEstimates
, lavInspect
,
modindices
# NOT RUN {
HS.model <- ' visual =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed =~ x7 + x8 + x9 '
fit <- cfa(HS.model, data=HolzingerSwineford1939)
summary(fit, standardized=TRUE, fit.measures=TRUE, rsquare=TRUE)
fitted(fit)
coef(fit)
resid(fit, type="normalized")
# }
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