Posterior intervals

Posterior intervals of all model parameters.

Usage

# S3 method for class 'blrmfit'
posterior_interval(object, prob = 0.95, ...)

Arguments

object

fitted model object

prob

central probability mass to report, i.e. the quantiles 0.5-prob/2 and 0.5+prob/2 are displayed. Multiple central widths can be specified.

...

not used in this function

Value

Matrix of two columns for the central probability interval prob for all parameters of the model.

Details

Reports the quantiles of posterior parameters which correspond to the central probability mass specified. The output includes the posterior of the hyper-parameters and the posterior of each group estimate.

Examples

.user_mc_options <- options()

example_model("single_agent", silent = TRUE)

posterior_interval(blrmfit)
#>                                                      2.5%     97.5%
#> mu_log_beta[log(drug_A/dref),intercept]        -1.4601463 4.3873983
#> mu_log_beta[log(drug_A/dref),log_slope]        -0.6559907 1.6527162
#> tau_log_beta[1,log(drug_A/dref),intercept]      0.0000000 0.0000000
#> tau_log_beta[1,log(drug_A/dref),log_slope]      0.0000000 0.0000000
#> rho_log_beta[log(drug_A/dref)]                 -0.9474960 0.9564961
#> beta_group[trial_A,log(drug_A/dref),intercept] -1.4601463 4.3873983
#> beta_group[trial_A,log(drug_A/dref),slope]      0.5189278 5.2211429

## Recover user set sampling defaults
options(.user_mc_options)