Added the argument exclude_xy_cov
and exclude_feedback to get_add()
and model_set(), for excluding paths
that create feedback loops, and
covariances involving a predictor
and an outcome variable (including
those linked by indirect paths).
Default values has been changed
to TRUE since 0.1.3.5. To
reproduce results from previous version,
set them to FALSE. (0.1.3.2, 0.1.3.5)
Added min_bpp_labelled to
model_graph(), to hide the labels
of models with small BPPs.
(0.1.3.5)
Added the argument drop_equivalent_models,
to model_set(). If TRUE, the
default, the models fitted will be
checked for equivalence. If two or
more more models are equivalent, only
one of them will be retained.
The groups of equivalent models identified,
and the models dropped, will be
printed by the print method. (0.1.3.9)
Added measurement_invariance_models(),
for generating metric and scalar
invariance models and their partial
invariance versions. (0.1.3.10 - 0.1.3.11)
Because it is very likely that users
would like to see come fit measures
along with BPPs, the default of
more_fit_measures of the print
method of model_set-class object
changed to c("cfi", "rmsea").
(0.1.3.7)
Revised fit_many() to support
multigroup models. (0.1.3.8)
A progress bar can be displayed when
model_set() is identifying nested
models. (0.1.3.13)
Shortened BIC Posterior Probability
to BPP in some sections of the
printout of print.model_set().
(0.1.3.14)
Cumulative BPPs no longer displayed
by default in print.model_set().
Print them by setting cumulative_bpp
to TRUE. (0.1.3.15)
Update an internal function to handle nonconvergence in checking nested relation. Only affect the graphs and only happen in some rare cases. (0.1.3.16)
The must_not_add argument should
work now for some parameters that may
not be recognized as interchangeable.
(0.1.3.1)
Fixed a bug in must_not_drop and
must_drop of get_drop(). They
should work properly now. (0.1.3.5)
Fixed a bug in model_graph().
Short names should now be properly
constructed. (0.1.3.3)
Fixed some bugs in print.model_set()
about the printing of additional fit
measures. (0.1.3.6, 0.1.3.7)
Fixed a bug in checking whether two models are equivalent. (0.1.3.12)
model_set()model_set() to work with
user-supplied models. These models
are supplied as parameter tables
through the argument partables.
(0.1.2.7)print-method of
model_set-class objects. Users can
set the prior probabilities of one or
more models of their choice. (0.1.2.7)c-method for partables-class
and model_set-class objects. For the
ease of adding user models when calling
model_set(). (0.1.2.7)lavaan-class objects)
to model_set() through the
argument sem_out. (0.1.2.17)print method of model_set()
supports printing additional fit
measures available from
lavaan::fitMeasures(). Check the
argument more_fit_measures.
(0.1.2.27)print method of model_set()
support printing short model names,
which can be used to interpret
the output of model_graph().
(0.1.2.29, 0.1.2.30)model_graph() to determine
nested relation using the method
by Bentler and Satorra (2010). This
can be done only if fixed.x
is set to FALSE. (0.1.2.10, 0.1.2.19)model_graph() if nested relations
need to be determined. (0.1.2.28)model_graph()model_graph() to plot
user-supplied models. (0.1.2.7)model_graph() with new options.
If drop_redundant_direct_paths
is TRUE (default), redundant
direct paths will be removed.model_graph().
(0.1.2.20)model_graph()
to label arrows by model df
differences (see label_arrow_by_df),
and weight arrow widths by
model df differences (see
weight_arrows_by_df). (0.1.2.20)partables-class object. (0.1.2.8)partables-class objects. (0.1.2.9, 0.1.2.12)model_graph()
to use short names in the
graph, if they are created and
stored by model_set().
(0.1.2.29, 0.1.2.30)lavaan::modificationIndices() about
equality constraints. (0.1.2.5)unique_models() to handle
user-supplied models. (0.1.2.6)model_set(). (0.1.2.11)print
method of partables. (0.1.2.13)model_set() will check whether
the sum of user-supplied prior
probabilities is less than 1. (0.1.2.14)print method of
model_set objects to print original
model dfs. (0.1.2.15)fit_many(), can set the
model with whichfit_many() will compute
model df difference. (0.1.2.16)model_set-class object to print
models that failed the past.check
of lavaan. (0.1.2.32)model_set() if no paths are dropped
or no paths are added. (0.1.2.3)gen_models()'s argument, output.tinytest for tests. (0.1.0.9004 - 0.1.0.9006)