Bioequivalence and Bioavailability Forum • evaluation of tmax: use of relative effects?

evaluation of tmax: use of relative effects? [Nonparametrics]

posted by martin – Austria, 2010-09-16 20:04 (4964 d 13:20 ago) – Posting: # 5920
Views: 20,091

dear d_labes and HS!

I spend some time on thinking how to compare tmax and have some doubts that using the difference between average values (e.g. medians, Hodges-Lehmann or Harrell-Davis estimate) is appropriate as the effect size in tmax between test and reference depends on the sampling times used.

For this reason I would suggest using relative effects (e.g. implemented in R package nparcomp).

Definition (taken from this presentation http://www.biopharmnet.com/doc/2010_05_20_webinar.pdf ):
"The relative effect is a a measure of how often a random subject receiving treatment X will outperform a random subject receiving treatment Y. It can be interpreted as a probability that a randomly selected patient in the control reveals a smaller response value than a randomly selected patient in the treatment group"

naive application of d_labes dataset:


npar.t.test(pdiff~sequence, conflevel = 0.1, data=PKt)



Nonparametric Behrens-Fisher Problem 

NOTE: 

*-----------Analysis of relative effects-----------* 

- Confidence interval for relative effect p(i,j)

     with confidence level 0.9 

- Method =  Delta-Method (Logit) 

- p.perm = p-value of the Neubert-Brunner permutation test 

- p-Values for  H_0: p(i,j)=1/2 

 

*----------------Interpretation--------------------* 

p(a,b) > 1/2 : b tends to be larger than a 

*-------------------Wilcox.Test--------------------* 

- Asymptotic Wilcoxon Test 

- In this setup you can only test H_0:F_i = F_j 

*--------------------------------------------------* 

$Data.Info

  Sample Size

1     RT    7

2     TR    7



$Analysis.of.relative.effects

  Comparison rel.effect confidence.interval   t.value p.value p.perm

1   p(RT,TR)      0.633   [ 0.354 ; 0.844 ] 0.7804535   0.435   0.41



$Wilcoxon.Test

  Comparison rel.effect   p.value

1   p(RT,TR)      0.633 0.4345742

what do you think about using relative effects for comparing tmax values between test and reference?

best regards

martin

Complete thread:

tmax in case of ties: R vs. R vs. SAS d_labes 2010-09-10 12:05
- tmax in case of ties: StatXact, Phoenix, and... Helmut 2010-09-10 18:28
  - Ties, no ties, ties, no ties ... d_labes 2010-09-13 13:21
    - simulation martin 2010-09-14 08:33
      - simulants of the world unite d_labes 2010-09-15 10:14
        
        simulants of the world unite martin 2010-09-15 14:53
        
        simulants of the world unite Helmut 2010-09-15 16:17
        
        simul ants with no ties d_labes 2010-09-16 11:19
        
        simul ants with no ties Helmut 2010-09-16 14:01
        
        two different approaches martin 2010-09-16 15:35
- evaluation of tmax: use of relative effects?martin 2010-09-16 18:04
  - Not positive about that Helmut 2010-09-16 19:52
    - Not positive about that martin 2010-09-16 21:00
      - Stupidity Helmut 2010-09-17 13:10
- tmax in case of ties: R vs. R vs. SAS Jack 2010-09-20 14:03
  - R packages Helmut 2010-09-20 14:20
    - R packages code d_labes 2010-09-27 11:27
    - R packages Jack 2010-09-27 16:14
  - Is Exact exact? d_labes 2010-09-27 09:53