Bugs fixed:
Major Feature:
glm
and glmer
without plot)Minor Feature:
cfa_summary
support path diagramefa_summary
rewrite using functions from parameters
and support post-hoc CFA testcfa_summary
support factor loading is hidden for same latent factor (only when group = NULL
)cor_test
and descriptive_table
support rich-text formatted table outputmodel_summary
rewrite using parameters::model_parameters
lm_summary
to integrated_model_summary
cor_test
re-write using the correlation package, so it supports more methods and robust standard errorsquite
and streamline
support in all models that print outputknit_to_Rmd
)Major Feature:
Minor Feature:
measurement_invariance
support multiple-factor model with tidyselect syntax model_summary_with_plot
support outlier detection model_performance
support a wider array of model performance measure cfa_summary
and measurement_invariance
support checking goodness of fit Bugs fixed
model_summary_with_plot
. You can no request simple_slope
and check_assumption
correctly. cor_test
is not exported requireNamespace()
Major Feature:
lme_model
, model_summary_with_plot
support tidyselect syntax cfa_summary
support multi-factor CFA with tidyselect syntax Minor Feature:
assumption_plot
to visually inspect assumptions for mixed effect models in model_summary_with_plot
two_way_interaction_plot
, three_way_interaction_plot
only require the model object to produce the plot. lme_model
, model_summary_with_plot
support using lme4
package. model_summary_with_plot
lme_model
support passing explicit model compare_fit
support more model comparison (e.g., lme, glme) Bugs fixed:
measurement_invariance
stop using semTools::compareFit
. Added a self-created compare_fit
function for the package papaja::apa_theme()
dependency. .data
from rlang
for mutate
function model_summary_with_plot
always return list and changed to logical (set to T to return result_list) model_summary_with_plot
return a named list object New Feature:
descriptive_table
support wider array of descriptive indicator (e.g., median, range) and missing & non_missing values count Bugs fixed:
cor_test
bug that the function return a correlation matrix with blank cells if the correlation is too high between the two items (rounded to 1).data_check
function that warns the users if non-numeric variables are coerced into numeric.