Calculate blinded statistical information

Estimates the blinded dispersion and event rate from aggregated interim data and calculates the observed statistical information for the log rate ratio, assuming the planned allocation ratio and treatment effect.

Usage

calculate_blinded_info(
  data,
  ratio = 1,
  lambda1_planning,
  lambda2_planning,
  event_gap = NULL
)

Arguments

data

A data frame containing the blinded interim data. Must include columns events (number of events) and tte (total exposure=follow-up time).

ratio

Planned allocation ratio (experimental / control). Default is 1.

lambda1_planning

Planned event rate for the control group.

lambda2_planning

Planned event rate for the experimental group.

event_gap

Optional. Gap duration (numeric) to adjust planning rates if provided. If provided, planning rates are adjusted as lambda / (1 + lambda * gap).

Value

A list containing:

blinded_info

Estimated statistical information.

dispersion_blinded

Estimated dispersion parameter (k).

lambda_blinded

Estimated overall event rate.

lambda1_adjusted

Re-estimated control rate.

lambda2_adjusted

Re-estimated experimental rate.

Examples

interim <- data.frame(events = c(1, 2, 1, 3), tte = c(0.8, 1.0, 1.2, 0.9))
calculate_blinded_info(
  interim,
  ratio = 1,
  lambda1_planning = 0.5,
  lambda2_planning = 0.3
)
#> $blinded_info
#> [1] 1.640582
#> 
#> $dispersion_blinded
#> [1] 1.617397e-05
#> 
#> $lambda_blinded
#> (Intercept) 
#>    1.794874 
#> 
#> $lambda1_adjusted
#> (Intercept) 
#>    2.243592 
#> 
#> $lambda2_adjusted
#> (Intercept) 
#>    1.346155 
#>