For every posterior draw, the groups are ranked by a chosen survival summary (median survival, survival at a fixed time, or RMST) and the frequency of each rank is returned. Useful as a decision aid: the row of the output for rank 1 gives the posterior probability that each group is the best.
Usage
rank_probabilities(
fit,
newdata = NULL,
function_of = "median",
times = NULL,
tmax = NULL,
...
)Arguments
- fit
A fitted `pooling_surv` object.
- newdata
Optional data frame with one row per group used to fix covariates. If `NULL`, covariates are set to zero.
- function_of
Character; one of `"median"`, `"survival"` (alias `"S_t"`), or `"rmst"`.
- times
Scalar time when `function_of = "survival"`.
- tmax
Positive horizon when `function_of = "rmst"`.
- ...
Unused.
Value
A data frame with columns `group`, `rank`, and `prob`. Rank 1 is the largest summary value (best group).
Examples
set.seed(2719)
trial_data <- simulate_data(n = 90, K = 3, censoring_rate = 0.3)
fit <- pooling_surv(survival::Surv(time, event) ~ group,
data = trial_data,
iter = 300, warmup = 150, chains = 2)
rank_probabilities(fit)
#> group rank prob
#> 1 1 1 0.010000000
#> 2 2 1 0.053333333
#> 3 3 1 0.936666667
#> 4 1 2 0.233333333
#> 5 2 2 0.706666667
#> 6 3 2 0.060000000
#> 7 1 3 0.756666667
#> 8 2 3 0.240000000
#> 9 3 3 0.003333333