Fixes
* Fixed anova plot labelling issue with two-way interaction
* Fixed model_summary print lm model summary when glm model is specified
* Fixed model summary cannot handle aov models
* Fixed the check_factorstructure function to import from performance instead of parameters package

Major Feature
* Added support for ANOVA plots (with continuous variable as moderator)
* Added support for polynomial plot (incl. curvilinear plots)
* Added support for Cronbach alpha computation (useful to combine with descriptive_table)

Minor Feature
* Integrate two-way and three-way interaction plot into one function

Fixes
* Fixed the issue that some model assumption checks were not printed
* Fixed the issue that compare_fit function not able to for comparing lm models

Fixes
* Fixed control variables must be numeric variables in interaction plots (i.e., added support for factor variables) * Simple slope no longer need to pass in the interaction_terms and data arguments
* Support multilevel modeling again after fixes introduced in insight package.

Fixes
* Drop support for multilevel modeling temporarily due to insight package recent non-backward compatible changes

Fixes
* Fixed bugs that measurement invariance does not have row name.

Major Feature
* Added support reliability measure summary
* Added support mediation models
* Added support generalized linear regression (glm and glmer without plot)

Minor Feature
* cfa_summary support path diagram
* efa_summary rewrite using functions from parameters and support post-hoc CFA test
* cfa_summary support factor loading is hidden for same latent factor (only when group = NULL)
* cor_test and descriptive_table support rich-text formatted table output * model_summary rewrite using parameters::model_parameters
* integrate summary with plot for lm_summary to integrated_model_summary * cor_test re-write using the correlation package, so it supports more methods and robust standard errors
* quite and streamline support in all models that print output
* Give instruction on how to use R Markdown (see knit_to_Rmd)

Major Feature
* Added support linear regression
* Added support exploratory factor analysis
* Complete overhaul to produce rich-text formatted summary output

Minor Feature
* measurement_invariance support multiple-factor model with tidyselect syntax
* model_summary_with_plot support outlier detection
* Changed data from EWCS_2015_shorten to popular (a data-set that is easier to understand)
* Added a new function that allow convert HTML to PDF function for knitting Rmd
* model_performance support a wider array of model performance measure
* cfa_summary and measurement_invariance support checking goodness of fit

Fixes
* Critical bug fix for model_summary_with_plot. You can no request simple_slope and check_assumption correctly.
* Critical bug fix that cor_test is not exported
* remove some packages from import and switch to requireNamespace()
* added fallback for normality check

Major Feature
* lme_model, model_summary_with_plot support tidyselect syntax
* cfa_summary support multi-factor CFA with tidyselect syntax

Minor Feature
* Added 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)

Fixes
* This current version build pass CMD check
* measurement_invariance stop using semTools::compareFit. Added a self-created compare_fit function for the package
* Remove papaja::apa_theme() dependency.
* Use .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

Fixes
* Fixed the 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).
* Add a data_check function that warns the users if non-numeric variables are coerced into numeric.

  • initial build