Used precomputed vignettes to reduce the package size and also the speed to build vignettes. (0.1.9.1)
est_change_raw() will now keep the original order of
parameters. (0.1.9.2)
Updated terms to match those used in the manuscript. (0.1.9.3)
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.
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