semfindr 0.1.4.1

semfindr 0.1.4

Added DOI of Pek and MacCallum in the DESCRIPTION. (0.1.1.1)
Added approx_check() to check whether the input object is supported by the approximate method. (0.1.1.2)
Added est_change_plot() and est_change_gcd_plot(), diagnostic plots for casewise influence on parameter estimates. (0.1.1.3)
Diagnostic plot functions revised to allow users to fully control elements drawn. (0.1.1.4)
Fixed typos and grammatical mistakes in help pages and vignettes. (0.1.1.5)
Fixed an invalid URI in a vignette (casewise_scores). (0.1.3)
Added the documentation for the return value of pars_id_to_lorg(). (0.1.4)

First public release.
Added skip_all_checks to lavaan_rerun(), allowing users to experiment lavaan_rerun() and other functions on models not officially supported.
Revised est_change() and est_change_raw() to support the use of operators (e.g., ~, =~) to select parameters.
Added badges and R CMD Check Action.
Updated est_change(), est_change_raw() and est_change_approx() to support models with labelled parameters. (0.1.0.9005)
Added 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)
Updated est_change_* functions to use pars_id() and pars_id_to_lorg(). (0.1.0.9007)
Modified lavaan_rerun() to use lavaan::lavaan() instead of update() as the default way to rerun. (0.1.0.9008).
Updated some of the tests. (0.1.0.9009)
Added more examples. (0.1.0.9010)
Updated documentation (e.g., README and DESCRIPTION). (0.1.0.9011)
Updated influence_stat() and the plot functions to support the approximate approach. (0.1.0.9012)
Updated documentation.

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.