Bioequivalence and Bioavailability Forum

calculation of 90% CI for continuous variable in clinical endpoint studies [General Statistics]

posted by GM – India, 2017-11-19 13:13 (2348 d 05:23 ago) – Posting: # 17992
Views: 4,898

Hello El-Maestro,

Thankyou for the reply.

❝

❝ the tradition is to use 80.00%-125.00% for a ratio of continuous variables. This makes extremely good sense under a certain set of assumptions.

❝

Is it possible for untransformed data also? If possible what are the limits i.e., 80-125 or 80-120.

❝ You refer to section 21 of the guidance, but this does not relate to continuous variables. It applies to dichotomous variables instead.

❝

Actually I need clarification on section 20 of the same guideline mentioned above. My apologies for mentioning wrong section earlier.

❝ Rule of thumb: For a difference, the acceptance range is symmetric. For a ratio the lower acceptance limit equals the reciprocal upper limit, naturally. Most BE issues you will come across have elements of both if logs are involved.

How can we will calculate 90% CI for ratio of means of untransformed continuous variable using PROC GLM in SAS.

Please help me in this regards.

Thankyou
GM.

—
Best Regards,
GM

Complete thread:

calculation of 90% CI for continuous variable in clinical endpoint studies GM 2017-11-17 04:55 [General Statistics]
- calculation of 90% CI for continuous variable in clinical endpoint studies ElMaestro 2017-11-18 21:17
  - calculation of 90% CI for continuous variable in clinical endpoint studiesGM 2017-11-19 12:13
    - calculation of 90% CI for continuous variable in clinical endpoint studies ElMaestro 2017-11-20 20:41
      - calculation of 90% CI for continuous variable in clinical endpoint studies GM 2017-11-21 06:02
        
        calculation of 90% CI for continuous variable in clinical endpoint studies DavidManteigas 2017-11-21 10:01

calculation of 90% CI for continuous variable in clinical endpoint studies [General Sta­tis­tics]

Complete thread:

calculation of 90% CI for continuous variable in clinical endpoint studies [General Statistics]