Hierarchical Bayesian ANOVA Models
BANOVA: Hierarchical Bayesian ANOVA Models
Estimation of BANOVA with a Bernoulli dependent variable
Estimation of BANOVA with a Binomial dependent variable
Build BANOVA models
Floodlight analysis based on BANOVA models
Mediation analysis based on BANOVA models
Extract BANOVA models
Mediation analysis with multiple possibly correlated mediators
Estimation of BANOVA with a Multinomial dependent variable
Estimation of BANOVA with a normally distributed dependent variable
Estimation of BANOVA with a ordered Multinomial response variable
Estimation of BANOVA with Poisson dependent variables
Function to print the table of effect sizes
Estimation of BANOVA models
Simple effects calculation
Estimation of BANOVA with T-distributin of the dependent variable
Function to display the convergence diagnostics
Create a matrix of output plots from a BANOVA object
Function to print the table of means
Function to print the table of p-values
Function to plot the trace of parameters
It covers several Bayesian Analysis of Variance (BANOVA) models used in analysis of experimental designs in which both within- and between- subjects factors are manipulated. They can be applied to data that are common in the behavioral and social sciences. The package includes: Hierarchical Bayes ANOVA models with normal response, t response, Binomial (Bernoulli) response, Poisson response, ordered multinomial response and multinomial response variables. All models accommodate unobserved heterogeneity by including a normal distribution of the parameters across individuals. Outputs of the package include tables of sums of squares, effect sizes and p-values, and tables of predictions, which are easily interpretable for behavioral and social researchers. The floodlight analysis and mediation analysis based on these models are also provided. BANOVA uses 'Stan' and 'JAGS' as the computational platform. References: Dong and Wedel (2017) <doi:10.18637/jss.v081.i09>; Wedel and Dong (2020) <doi:10.1002/jcpy.1111>.