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Updated user_change_raw() to allow for user
functions that return an unnamed vector. Also added a
pkgdown website article for user_change_raw().
(0.1.8.5)
For lavaan_rerun(), added the argument
ncores to make it easier to set the number of CPU cores to
use in parallel processing. (0.1.8.7)
For lavaan_rerun(), added the option to show a
progress bar (generated by pbapply) by setting
progress to TRUE. Enabled by default.
(0.1.8.8)
Added on.exit() such that workers will be stopped if
lavaan_rerun() terminates abnormally. (0.1.8.2)
Updated some default values of approx_check() to
reflect new features added to other functions. (0.1.8.4)
Fixed a few Rd issues on CRAN. (0.l.8.6)
Print a more conservative estimate of the expected time. (0.1.8.7)
Remove an invalid link in the reference. (0.1.8.9)
index_plot() when the extracted column
has no names. (0.1.8.1)lavaan functions.
(0.1.6.1)lavaan_rerun().
(0.1.6.2)Added index_plot() for generating an index plot for
an arbitrary statistic. (0.1.5.5)
Added user_change_raw() for computing case influence
on user statistics. (0.1.5.8)
pars_id(). Users can now use the internal
lavaan group labels (e.g., ".g2",
".g3") to denote parameters in a group. This method is not
recommended (noted in the help page) but is included as an option.
(0.1.5.2)lavaan::lavCor() to estimate means and correlations
for Mahalanobis distance when missing data is present. The package
norm2 is no longer needed nor suggested. (0.1.5.4)README.md. (0.1.5.7)est_change(),
est_change_raw(), est_change_approx(), and
est_change_raw_approx(). (0.1.4.3, 0.1.4.16, 0.1.4.18,
0.1.4.19, 0.1.4.20)fit_measures_change() and
fit_measures_change_approx(). (0.1.4.4, 0.1.4.16)mahalanobis_rerun() and
mahalanobis_predictors() (0.1.4.5-0.1.4.6, 0.1.4.16,
0.1.4.18)influence_stat(). (0.1.4.7)":=" to
pars_id(). (0.1.4.13)pkgdown site. (0.1.4.1)approx_check() will check if the model has at least one
equality constraint. (0.1.4.2)pars_id(). (0.1.4.12)pgkdown
websites. (0.1.4.15)print.lavaan_rerun(), keep the format of lavaan
warnings. (0.1.4.17)fit_measures_change_approx() only supports
selected fit measures. (0.1.4.21)cutoff_change and largest_change to
est_change_gcd_plot(). (0.1.4.22)approx_check() to check whether the input object
is supported by the approximate method. (0.1.1.2)est_change_plot() and
est_change_gcd_plot(), diagnostic plots for casewise
influence on parameter estimates. (0.1.1.3)pars_id_to_lorg(). (0.1.4)skip_all_checks to lavaan_rerun(),
allowing users to experiment lavaan_rerun() and other
functions on models not officially supported.est_change() and est_change_raw()
to support the use of operators (e.g., ~, =~)
to select parameters.est_change(), est_change_raw() and
est_change_approx() to support models with labelled
parameters. (0.1.0.9005)pars_id() and pars_id_to_lorg() for
converting parameter specification to identification numbers ( positions
in the vector of coefficients or row numbers in the parameter tables).
(0.1.0.9006)est_change_* functions to use
pars_id() and pars_id_to_lorg().
(0.1.0.9007)lavaan_rerun() to use
lavaan::lavaan() instead of update() as the
default way to rerun. (0.1.0.9008).influence_stat() and the plot functions to
support the approximate approach. (0.1.0.9012)Added more vignettes.
lavaan_rerun() can accept an output with
inadmissible estimates. Disabled by default. Can be enabled by setting
allow_inadmissible to TRUE.
Added a print method for the lavaan_rerun()
class.
Added mahalanobis_predictors() to compute the
Mahalanobis distance using only the observed predictors.
Both mahalanobis_predictors() and
mahalanobis_rerun() support datasets with missing
data.
lavaan_rerun() can specify cases to exclude and
rerun by specifying the case IDs or selecting cases based on Mahalanobis
distance on all observed variables or on residuals of observed variables
in a path model.
Used lavaan::update() in lavaan_rerun. This is more
reliable than recreating the call.
Added implied_scores(). It supports only
single-group path analysis models for now.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.