Summarise basic parameter estimates from an msmbayes model

Summarise basic parameter estimates from an msmbayes model

Usage

# S3 method for msmbayes
summary(object, log = FALSE, time = FALSE, ...)

Arguments

object

Object returned by msmbayes.

log

Present log transition intensities and log hazard ratios, rather than transition intensities and hazard ratios.

time

Present inverse transition intensities (i.e. mean times to events)

...

Further arguments passed to both qdf and loghr.

Value

A data frame with one row for each basic model parameter, plus rows for the mean sojourn times. The posterior distribution for the parameter is encoded in the column value, which has the rvar data type defined by the posterior package. This distribution can be summarised in any way by calling summary again on the data frame (see the examples).

A string summarising a sample from the prior distribution, as a median and 95% equal-tailed credible interval, is given in the prior column.

Transition intensities, or transformations of transition intensities, are those for covariate values of zero.

Remaining parameters (in non-HMMs) are log hazard ratios for covariate effects.

See also

qdf, hr, loghr, posterior::summarise_draws

Examples

summary(infsim_model)
#> # A tibble: 4 × 6
#>   name   from    to      value prior             rhat
#>   <chr> <int> <int> <rvar[1d]> <chr>            <dbl>
#> 1 q         1     2  0.67 ± NA 0.14 (0.0031, 6)    NA
#> 2 q         2     1  3.86 ± NA 0.14 (0.0031, 6)    NA
#> 3 mst       1    NA  1.50 ± NA 7.4 (0.17, 326)     NA
#> 4 mst       2    NA  0.26 ± NA 7.4 (0.17, 326)     NA
summary(summary(infsim_model))
#>   name from to            prior rhat      mean    median sd mad        q5
#> 1    q    1  2 0.14 (0.0031, 6)   NA 0.6661110 0.6661110 NA   0 0.6661110
#> 2    q    2  1 0.14 (0.0031, 6)   NA 3.8606671 3.8606671 NA   0 3.8606671
#> 3  mst    1 NA  7.4 (0.17, 326)   NA 1.5012514 1.5012514 NA   0 1.5012514
#> 4  mst    2 NA  7.4 (0.17, 326)   NA 0.2590226 0.2590226 NA   0 0.2590226
#>         q95 rhat ess_bulk ess_tail
#> 1 0.6661110   NA       NA       NA
#> 2 3.8606671   NA       NA       NA
#> 3 1.5012514   NA       NA       NA
#> 4 0.2590226   NA       NA       NA
summary(summary(infsim_model), median, ~quantile(.x, 0.025, 0.975))
#>   name from to            prior rhat    median      2.5%
#> 1    q    1  2 0.14 (0.0031, 6)   NA 0.6661110 0.6661110
#> 2    q    2  1 0.14 (0.0031, 6)   NA 3.8606671 3.8606671
#> 3  mst    1 NA  7.4 (0.17, 326)   NA 1.5012514 1.5012514
#> 4  mst    2 NA  7.4 (0.17, 326)   NA 0.2590226 0.2590226