gsDesignNB (version 0.2.6)

unblinded_ssr: Unblinded sample size re-estimation for recurrent events

Description

Estimates the event rates and dispersion from unblinded interim data and calculates the required sample size to maintain power, assuming the planned treatment effect holds (or using the observed control rate).

Usage

unblinded_ssr(
  data,
  ratio = 1,
  lambda1_planning,
  lambda2_planning,
  rr0 = 1,
  power = 0.8,
  alpha = 0.025,
  accrual_rate,
  accrual_duration,
  trial_duration,
  dropout_rate = 0,
  max_followup = NULL,
  event_gap = NULL
)

Value

A list containing:

n_total_unblinded

Re-estimated total sample size using unblinded estimates.

dispersion_unblinded

Estimated dispersion parameter (k) from unblinded data.

lambda1_unblinded

Estimated control event rate from unblinded data.

lambda2_unblinded

Estimated experimental event rate from unblinded data.

info_fraction

Estimated information fraction at interim (unblinded information / target information).

unblinded_info

Estimated statistical information from the unblinded interim data.

target_info

Target statistical information required for the planned power.

Arguments

data

A data frame containing the unblinded interim data. Must include columns events (number of events), tte (total exposure/follow-up time), and treatment (treatment group identifier, e.g., 1 for control, 2 for experimental). This is typically the output of cut_data_by_date().

ratio

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

lambda1_planning

Planned event rate for the control group used in original calculation.

lambda2_planning

Planned event rate for the experimental group used in original calculation.

rr0

Rate ratio under the null hypothesis (lambda2/lambda1). Default is 1.

power

Target power (1 - beta). Default is 0.8.

alpha

One-sided significance level. Default is 0.025.

accrual_rate

Vector of accrual rates (patients per unit time).

accrual_duration

Vector of durations for each accrual rate. Must be same length as accrual_rate.

trial_duration

Total planned duration of the trial.

dropout_rate

Dropout rate (hazard rate). Default is 0.

max_followup

Maximum follow-up time for any patient. Default is NULL (infinite).

event_gap

Gap duration after each event during which no new events are counted. Default is NULL (no gap).

Examples

interim <- data.frame(
  events = c(1, 2, 1, 3),
  tte = c(0.8, 1.0, 1.2, 0.9),
  treatment = c("Control", "Control", "Experimental", "Experimental")
)
unblinded_ssr(
  interim,
  ratio = 1,
  lambda1_planning = 0.5,
  lambda2_planning = 0.3,
  power = 0.8,
  alpha = 0.025,
  accrual_rate = 10,
  accrual_duration = 12,
  trial_duration = 18
)