Bioequivalence and Bioavailability Forum • Getting variance components

Getting variance components [🇷 for BE/BA]

posted by StatR – Turkey, 2017-02-08 09:41 (3403 d 12:19 ago) – Posting: # 17033
Views: 22,174

Hi again d_labes,

I tried to find the correct model by the post you referred.

❝ In the older package nlme / lme() you may formulate the model similar to the FDA code. See that post.

Unfortunately, I am confused after reading tons of post, and I could not figure out what is "trt", "tmt" ... Simply, my data is as follows

 Subject Formula Period Sequence     Yijk

       1       1      1        1 4.933014

       1       0      2        1 5.006829

       1       1      3        1 4.854162

       1       0      4        1 5.081755

       2       1      1        1 4.854738

       2       0      2        1 4.690311

Where Yijk is the PK characteristic. The first sequence represents "TRTR" and the second sequence: "RTRT". In the formula 1 = T and 0 = R. In the referred post you say that

model2 <- lme(y~ drug + prd + seq,

# this random statement fits a symmetric positive definite covariance matrix,

# identical to UN in SAS???

                random= ~ tmt-1|subj,

                #different within variabilities                 

                weights=varIdent(form = ~ 1 | drug),

                data=BlaBla, method="REML")

In your model y = Yijk, drug=Formula, prd=Period, seq=Sequence,
but what is tmt? Also, is the my data format correct for the lme? Or, Should I change Formula as 1 = T, 2 = R and Sequence as 1 = TRTR, 2 = RTRT? Could you please make me clear.

Best.

Complete thread:

Bear vs. Phoenix & SAS Helmut 2015-04-20 17:34
- 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 lsmeans Helmut 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 componentsStatR 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