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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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.