# Convert enrollment and failure rates from `sim_fixed_n()`

to `sim_pw_surv()`

format

Source: `R/to_sim_pw_surv.R`

`to_sim_pw_surv.Rd`

`to_sim_pw_surv()`

converts failure rates and dropout rates entered in
the simpler format for `sim_fixed_n()`

to that used for `sim_pw_surv()`

.
The `fail_rate`

argument for `sim_fixed_n()`

requires enrollment rates,
failure rates hazard ratios and dropout rates by stratum for a 2-arm trial,
`sim_pw_surv()`

is in a more flexible but less obvious but more flexible
format. Since `sim_fixed_n()`

automatically analyzes data and `sim_pw_surv()`

just produces a simulation dataset, the latter provides additional options
to analyze or otherwise evaluate individual simulations in ways that
`sim_fixed_n()`

does not.

## Value

A list of two data frame components formatted for
`sim_pw_surv()`

: `fail_rate`

and `dropout_rate`

.

## Examples

```
# Example 1
# Convert standard input
to_sim_pw_surv()
#> $fail_rate
#> stratum period treatment duration rate
#> 1 All 1 control 3 0.07701635
#> 2 All 2 control 100 0.03850818
#> 3 All 1 experimental 3 0.06931472
#> 4 All 2 experimental 100 0.02310491
#>
#> $dropout_rate
#> stratum period treatment duration rate
#> 1 All 1 control 3 0.001
#> 2 All 2 control 100 0.001
#> 3 All 1 experimental 3 0.001
#> 4 All 2 experimental 100 0.001
#>
# Stratified example
fail_rate <- data.frame(
stratum = c(rep("Low", 3), rep("High", 3)),
duration = rep(c(4, 10, 100), 2),
fail_rate = c(
.04, .1, .06,
.08, .16, .12
),
hr = c(
1.5, .5, 2 / 3,
2, 10 / 16, 10 / 12
),
dropout_rate = .01
)
x <- to_sim_pw_surv(fail_rate)
# Do a single simulation with the above rates
# Enroll 300 patients in ~12 months at constant rate
sim <- sim_pw_surv(
n = 300,
stratum = data.frame(stratum = c("Low", "High"), p = c(.6, .4)),
enroll_rate = data.frame(duration = 12, rate = 300 / 12),
fail_rate = x$fail_rate,
dropout_rate = x$dropout_rate
)
# Cut after 200 events and do a stratified logrank test
sim |>
cut_data_by_event(200) |> # Cut data
wlr(weight = fh(rho = 0, gamma = 0)) # Stratified logrank
#> $method
#> [1] "WLR"
#>
#> $parameter
#> [1] "FH(rho=0, gamma=0)"
#>
#> $estimate
#> [1] 0.269558
#>
#> $se
#> [1] 7.030336
#>
#> $z
#> [1] -0.03834212
#>
#> $info
#> [1] 49.92
#>
#> $info0
#> [1] 50
#>
```