Summarise a Bayesian model — bayes

Produce a table summarising Bayesian models

Usage

bayes_results(model, logger = NULL)

covariate_results(...)

baseline_results(...)

Arguments

model: list. Output produced by baseline_model(), bayes_model() or covariate_model().
logger: Stores all notification messages to be displayed in the Log Window. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL
...: Parameters passed to bayes_results()

Value

HTML summary of the model

Examples

configured_data_path <- system.file("extdata", "configured_data.Rds", package = "metainsight")
configured_data <- readRDS(configured_data_path)

# n_adapt and n_iter are set low to run quickly, but should be left as the
# default values in real use

fitted_bayes_model <- bayes_model(configured_data = configured_data,
                                  n_adapt = 100,
                                  n_iter = 100)

bayes_results(fitted_bayes_model)
#> The results are on the Mean Difference scale.<br/><br/>Iterations = 101:200<br/>Thinning interval = 1<br/>Number of chains = 4<br/>Sample size per chain = 100