- Changed Depends field from R (>= 3.4.0) to R (>= 3.5.0) because of dependency on mvtnorm package.
- Fixed bug in how composite score indicators are assigned for higher-order factors. Previous code did not distinguish between indicator paths and regression paths.
- Added
get_factor_score_validity_se
function to return factor score standard errors. - Added
get_model_names
function to return a list of model variable names.
- Added
get_factor_score_coefficients
function to return factor score coefficients - Added
get_factor_score_validity
function to return factor score validity coefficients - Added
v_factor_score_disturbance
andv_factor_score_residual
tov_names
list returned bysim_standardized_matrices
. - The
v_factor_score
list now only returns factor score names associated with the latent variables.
- Can specify a mean and standard deviation in the
add_composite_scores
andadd_factor_scores
functions. - The
add_factor_scores
function now appends_FS
to the factor score names.
- Added
get_model_implied_correlations
function, which returns the model-implied correlation matrix of observed variables, latent variables, error terms, factor scores, and composite variables.
- Added
composite_score_validity
to list returned bysim_standardized_matrices
- Added
add_composite_scores
function to add composite scores to new data.
- Fixed bug that prevents computation of composite scores of third-order and fourth-order latent variables.
- Added the
matrix2lavaan
function to provide a convenient method of creating lavaan syntax from matrices. - Added the
lav2ram
function to extract standardized RAM matrices from a lavaan object. - The
sim_standardized_matrices
function has a new argument,composite_threshold
. If this argument is specified, variables with loadings below the threshold are not used as indicators of the composite scores. - Removed the semPlot package from suggests list
- Fixed the method of finding indicators for composite variables. A composite now is only created from direct indicators unless the latent variable is a higher-order factor with no direct indicators.
- Added the
fixed2free
function, which takes alavaan
syntax model with fixed parameters and returns alavaan
syntax model in which all parameters are free. - Added the
model_complete
function, which takes alavaan
syntax model with standardized loadings, structure coefficients, and covariances, and returns alavaan
syntax model with all standardized coefficients, including standardized variances. - Added the
add_factor_scores
function, which adds predicted factor scores to a data.frame.
- Initial release