BANOVA v1.2.0 (Release date: 2021-04-26)
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* Set half-Cauchy priors for all variance parameters

BANOVA v1.1.9 (Release date: 2020-12-16)
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* Added BANOVA.multi.mediation, a function for mediation analysis with multiple mediators
* Added models for analysis of Multivariate Normal and Truncated Normal dependent variables
* Fixed a bug in BANOVA.mediation related to mediated moderation
* Updated help functions

BANOVA v1.1.8 (Release date: 2020-07-23)
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* Added BANOVA.simple, a simple effects calculation for moderated variables
* Fixed a bug in data pre-processing related to labelling of dummy and effects coded variables
* Fixed a bug related to ANOVA table of a single level Multinomial models

BANOVA v1.1.7 (Release date: 2020-04-10)
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* Fixed a bug related to the class function updates

BANOVA v1.1.6 (Release date: 2020-01-12)
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* The default prior for single level models is changed to weakly informative N(0, 100)

BANOVA v1.1.5 (Release date: 2019-12-31)
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* Fixed a bug related to the recent R update (as.matrix)
* Updated the effect size formula using deviance residuals for Poisson, Binomial, etc.

BANOVA v1.1.4 (Release date: 2019-08-11)
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* Added 'library(rstan)' to the manual to fix a bug in running BANOVA.run on R 3.6.0+

BANOVA v1.1.3 (Release date: 2019-06-23)
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* Fixed a bug in the table predictions for the ordered logit model
* Update the manual with the new id assignment in the function BANOVA.run 
* Remove the system requirement for JAGS installation, JAGS based functions are not recommended

BANOVA v1.1.2 (Release date: 2019-01-21)
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* Fixed the problem with large effect sizes by including the level-1 error term
* Enable the calculation of the posterior distribution of planned comparisons
* Output the distribution of indirect effects in mediation across respondents
* Fixed the bug related to id input and output 

BANOVA v1.1.1 (Release date: 2018-01-21)
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* Added vignettes

BANOVA v1.1.0 (Release date: 2018-01-04)
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* Added R2 measure of fit
* Added level-1 variance term to the calculation of R2 and effect sizes
* Added p values and effect sizes for indirect effects 
* BANOVA mediation only prints indirect effects, users can still access direct effects through the dir_effects element
* BANOVA mediation for Multinomial models is under development
* Use 3 decimals for the 95%CI of the effect sizes
* Default settings for MCMC burn-in=5000, sample=2000, thin=10
* Other variables in the model are included in the output of floodlight analysis
* Users can set up values for other numeric variables for the floodlight analysis

BANOVA v1.0.0 (Release date: 2017-11-02)
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* add seeds for replications 

BANOVA v0.9.1 (Release date: 2017-08-26)
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* single level models are supported for old models except Binomial and Bernoulli
* fix the bug that the interaction between the mediator and moderators is missing in the mediation output
* The names in the table of indirect effets are reordered (alphabetically)

BANOVA v0.9 (Release date: 2017-06-27)
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* BANOVA uses Stan!
* all two-level models are moved into a simple function call: BANOVA.run 
* old two-level models (e.g. BANOVA.Normal, BANOVA.Bin, etc.) are still kept, but will be removed gradually
* single level models are included

BANOVA v0.8 (Release date: 2016-12-12)
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* change the name 'table of means' to 'table of predictions'
* column names of the data goalstudy are changed to make more sense
* add floodlight analysis
* add mediation analysis (single mediator, multiple moderators)

BANOVA v0.7 (Release date: 2016-08-24)
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* Exclude numeric variables for predictions
* Change the format of convergence diag.
* Change the calculations in the table of means and predictions to exp(mu + sigma^2/2) instead of exp(mu) for the Poisson model
* Table of means is now included in the summary
* Use 4 digits for the outputs in the summary except the table of means
* Median is changed to mean in the output of table of means
* Predictors that have 3 levels or fewer will be automatically considered as factors

BANOVA v0.6 (Release date: 2016-08-01)
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* Check missing data for independent variables
* Fix typos
* Add warnings for mean centering of numeric variables
* Print full convergence diag. for the Heidelberg and Welch diagnostic.
* Table of means can now print any level of interactions