The blavaan
class contains the lavaan
class, representing a (fitted) Bayesian 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.
Objects can be created via the
bcfa
, bsem
, bgrowth
or
blavaan
functions.
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. No longer used.
boot
:List. Unused for Bayesian models.
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. Includes Stan or JAGS objects used for MCMC.
signature(object = "blavaan", 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
covariance matrix of the estimated parameters.
signature(object = "blavaan")
: Print a short summary
of the model fit
% \item{plot}{\code{signature(object = "blavaan")}: S4 method for % creating plots. Also see \code{?plot.blavaan}.}
signature(object = "blavaan", header = TRUE,
fit.measures = FALSE, estimates = TRUE, ci = TRUE,
standardized = FALSE, rsquare = FALSE, std.nox = FALSE,
psrf = TRUE, neff = FALSE, postmedian = FALSE, postmode = FALSE,
priors = TRUE, bf = 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 standardized = TRUE
,
the standardized solution is also printed. Note that SEs and
tests are still based on unstandardized estimates. Use
standardizedSolution
to obtain SEs and test
statistics for standardized estimates.
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 psrf = TRUE
, potential scale reduction factors (Rhats)
are printed.
If neff = TRUE
, effective sample sizes are printed.
If postmedian
or postmode
are TRUE, posterior
medians or modes are printed instead of posterior means.
If priors = TRUE
, parameter prior distributions are
printed.
If bf = TRUE
, Savage-Dickey approximations of the Bayes
factor are printed for certain parameters.
Nothing is returned (use
lavInspect
or another extractor function
to extract information from a fitted model).
Edgar C. Merkle, Ellen Fitzsimmons, James Uanhoro, & Ben Goodrich (2021). Efficient Bayesian Structural Equation Modeling in Stan. Journal of Statistical Software, 100(6), 1-22. URL http://www.jstatsoft.org/v100/i06/.
Edgar C. Merkle & Yves Rosseel (2018). blavaan: Bayesian Structural Equation Models via Parameter Expansion. Journal of Statistical Software, 85(4), 1-30. URL http://www.jstatsoft.org/v85/i04/.
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/.
bcfa
, bsem
, bgrowth
if (FALSE) {
HS.model <- ' visual =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed =~ x7 + x8 + x9 '
fit <- bcfa(HS.model, data=HolzingerSwineford1939)
summary(fit, standardized=TRUE, fit.measures=TRUE, rsquare=TRUE)
coef(fit)
}
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