Search results

  1. P

    Sample size calculation for survival clinical trial

    Hi! I need to calculate sample size for phase 3 clinical trila with following assumption: Primary Endpoint: Overall Survival (OS) in 36 months; Study Hypothesis: superiority (H0: Υ ≥ δ; H1: Υ < δ); Type I error: 2.5% (α = 0.025); Type II error: 20% (β = 0.2); Expected HR for...
  2. P


    Hello everyone! I will plan a clinical trial, double-blinded, phase 3, that long 24 weeks, and the primary endpoint will be assessed based on results at Week 12. And I want to add one interim analysis when all patients finished week 12, and conduct a final analysis when patients finished the...
  3. P

    Sample size calculation

    Hi everyone! Can anyone helps with calculation sample size for trial? We are planned 2/3 phase with group-sequential design (two stage) with re-estimation procedure for some rare disease (to prove superiority), expected succes rate in treatment group is around 85%, and 75% for control group...
  4. P

    Block randomization

    Hello everyone! Does anyone know packages or functions on R with which you can do block randomization with allocation ratio 3:1?
  5. P

    Sample size for observational study

    Hi everyone! I should to calculate sample size for observational study in that the primary endpoint is to assess the distribution of COPD by 4 classess (COLD). According to article i know expected distribution by class: 1 class: 16% 2 class: 25% 3 class: 28% 4 class: 31% How I may to estimate...
  6. P

    Control the type 1 error

    Hello, everyone! In my reasearch I have two primary endpoints - overall survival and progression-free survival. I test the superiority hypothesis H0: hazard ratio more than superiority margin and Ha is hazard ratio is less than superiority margin. And my question is: What method of control type...
  7. P

    Help with sample size for overall survival endpoint

    Hi everyone! Please help to calculate sample size for primary endpoint - overall survival after 36 months. It is a superiority hypothesis: H0: ϒ ≥ δ and H1: ϒ < δ, where ϒ- hazard ratio, δ- superiority margin. Type I error: 2.5%, Type II error: 20% (β=0.2), expected hazard ratio for tested and...