Changelog

Source: NEWS.md

betaselectr 0.2.3.1.1

Improvement

• lm_betaselect() and glm_betaselect() can accept the output of lm() or glm() as the input. The call stored in lm() and glm() will be retrieved to run lm_betaselect() or glm_betaselect(). (0.2.2.2)

Miscellaneous

• Updated to work with tibble. (0.2.2.1)

• Fixed a harmless bug in lm_betaselect() and glm_betaselect(). Previously, if .all., then all numeric variables in the input dataset will be standardized, including those not used in the model. This would not affect the results because these variables are used anyway. Fixed and only variables used in the model will be standardized. (0.2.3.1)

betaselectr 0.2.2

CRAN release: 2026-07-11

Miscellaneous

• Updated to accommodate a change in a forthcoming version of lavaan (0.7-1). (0.2.2)

betaselectr 0.2.1

CRAN release: 2026-06-09

Miscellaneous

• Updated the documentation with the related manuscript.

betaselectr 0.1.4

CRAN release: 2026-04-07

Improvement

• The print method of the output of lav_betaselect() has a column to indicate whether a parameter is unstandardized. (0.1.3.1)

• The computation of the standardized solution with bootstrapping now supports parallel processing. (0.1.3.2)

betaselectr 0.1.3

CRAN release: 2025-10-29

New Features

• lav_betaselect() can also compute the “standardized” intercepts, though in the same way lavaan does, by dividing an intercept by the standard deviation of the outcome variable (the y variable). This can be enabled by setting std_intercept to TRUE (FALSE by default). (0.1.2.1)

Improvement

• lav_betaselect() will no longer check whether variables involved in a product term have been mean-centered by default (but can still be enabled if necessary). The coefficient of the so-called “main effect” term of these variables will now be computed correctly even without mean-centering. (0.1.2.1, 0.1.2.2)

Miscellaneous

• lav_betaselect() will not compute the coefficients of covariances and variances that involve a product term, if the variables involved are not mean-centered. Without mean-centering, it is impossible to compute them if the joint distribution of the variables is not multivariate normal. (0.1.2.1)

betaselectr 0.1.2

CRAN release: 2025-05-02

Miscellaneous

• Added a few more tests for one-IV models. (0.1.2)

Bug Fixes

• lav_betaselect(): The standardized coefficients of the component variables of a product term are incorrect if mean-centering is not done. For now, lav_betaselect() will check whether they are mena-centered. If not, it will raise an error and suggest users to mean-center the involved variables first. (0.1.1)

betaselectr 0.1.0

CRAN release: 2024-11-11

• First version to CRAN.