Bioequivalence and Bioavailability Forum • info for lsmeans

info for lsmeans [🇷 for BE/BA]

posted by Helmut – Vienna, Austria, 2015-04-21 03:15 (3725 d 01:08 ago) – Posting: # 14726
Views: 24,807

Hi Yung-jin,

❝ I like to thank you for this post first

Welcome.

❝ (very nice codes).

I would never (!) use such a code given the nice vectorization possible in R. It was only intended as an example to get the means without a model.

❝ But do you think that we should also present df, upper/lower CI (90% or 95%), and p values stuffs for lsmean?

IMHO, the df makes sense since it tells us whether we pulled the right stuff from the model.
The CI is nice to know but not necessary. If the CIs overlap there is no significant difference between treatments. So what? No agency asks for it.
I never understood the purpose of the t- and p-values. What is tested here? A difference to zero or what?

❝ Or just keep it simple as you suggest?

Please don’t think about using this awful code!

—
Dif-tor heh smusma 🖖🏼 Довге життя Україна!
Helmut Schütz

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Science Quotes

Complete thread:

Bear vs. Phoenix & SAS Helmut 2015-04-20 17:34 [🇷 for BE/BA]
- R vs. Phoenix & SAS? yjlee168 2015-04-20 19:36
  - R vs. Phoenix & SAS? Helmut 2015-04-21 01:02
    - lme() does not work with all fixed effects yjlee168 2015-04-21 23:41
      - lme() does not work with all fixed effects Astea 2016-11-04 00:13
        
        lmer: Method B (PE catched for imbalanced dataset!!!) and Method C mittyri 2016-11-05 17:38
        
        lmer: Method B (PE catched for imbalanced dataset!!!) and Method C Astea 2016-11-05 19:27
        
        lmer: Method B is ready for scaling mittyri 2016-11-05 20:01
        
        lmer: Method B is ready for scaling Astea 2016-11-06 11:50
        
        lmer: Method B is ready for scaling mittyri 2016-11-07 06:07
- info for lsmeans yjlee168 2015-04-20 21:34
  - info for lsmeansHelmut 2015-04-21 01:15
    - once more about R and replicate designes Astea 2016-11-02 23:43
      - once more about R and replicate designes VStus 2016-11-06 11:34
        
        Getting variance components from the lmer output StatR 2017-02-03 13:53
        
        Getting variance components from the lmer output VStus 2017-02-03 15:47
        
        Getting variance components from the lmer output StatR 2017-02-03 17:12
        
        Getting variance components d_labes 2017-02-07 11:16
        
        Getting variance components StatR 2017-02-07 11:36
        Getting variance components StatR 2017-02-08 08:41
        
        Getting variance components d_labes 2017-02-08 10:13
        
        Getting variance components StatR 2017-02-08 10:19
        
        Data structure Helmut 2017-02-08 10:33
        
        Data structure StatR 2017-02-08 10:49