Bioequivalence and Bioavailability Forum • gls() for unequal variances?

gls() for unequal variances? [🇷 for BE/BA]

posted by d_labes – Berlin, Germany, 2010-04-26 18:36 (5532 d 22:40 ago) – Posting: # 5238
Views: 62,548

Dear Helmut,

❝ ... I would go with Welch-tests, because ANOVA (or lm and lme) assume

❝ homoscedasticity.

What about:

require(nlme) # HS: added, because not loaded by default

# must use gls() because lme() does not allow for no random effect

glsModel <- gls(lnAUC0t ~ drug, weights=varIdent(form=~1|drug), data=TotalData)

summary(glsModel)

This gives (20 subjects bear data) :

Generalized least squares fit by REML

  Model: lnAUC0t ~ drug 

  Data: TotalData 

       AIC      BIC    logLik

  8.491722 12.05321 -0.245861



Variance function:

 Structure: Different standard deviations per stratum

 Formula: ~1 | drug 

 Parameter estimates:

        1         2 

1.0000000 0.4173818  (seems to give us different variances as portion of residual, hurrrrah)



Coefficients:

              Value Std.Error  t-value p-value

(Intercept) 7.10189 0.1056507 67.22045  0.0000

drug2       0.01594 0.1144841  0.13923  0.8908

But astonishing :confused:

intervals(glsModel, level=0.9)

Approximate 90% confidence intervals



 Coefficients:

                 lower    est.     upper

(Intercept)  6.9186849 7.10189 7.2850951

drug2       -0.1825826 0.01594 0.2144626



#back-transformed

T vs. R       83.31   101.61   123.92 (same as without weights or lm() )

—
Regards,

Detlew

Complete thread:

Parallel bears meeting at random in infinity d_labes 2010-04-22 11:43
- Parallel bears meeting at random in infinity ElMaestro 2010-04-22 12:53
  - Parallel groups in bear - CIs d_labes 2010-04-22 14:00
    - Parallel groups in bear - CIs ElMaestro 2010-04-22 21:47
      - Parallel groups in bear - CIs d_labes 2010-04-23 09:09
    - Parallel groups in bear - CIs yjlee168 2010-04-25 23:29
- Parallel bears meeting at random in infinity yjlee168 2010-04-22 23:09
  - Modelling Parallel bears d_labes 2010-04-23 09:12
    - Modelling Parallel bears yjlee168 2010-04-23 21:14
      - Validating vs. WinNonlin... Helmut 2010-04-24 00:28
        
        Validating vs. WinNonlin... yjlee168 2010-04-24 19:36
        Validating vs. WinNonlin... yjlee168 2010-04-26 00:09
        
        Validating vs. WinNonlin... Helmut 2010-04-26 01:29
        
        WNL in replicate BE yjlee168 2010-04-26 08:59
        
        WNL in replicate BE Helmut 2010-04-26 16:15
      - Modelling Parallel bears yjlee168 2010-04-25 19:34
        
        Modelling Parallel bears ElMaestro 2010-04-25 20:40
        Dataset Helmut 2010-04-25 22:38
        
        Dataset yjlee168 2010-04-25 22:44
        
        Dataset Helmut 2010-04-26 01:13
        
        Dataset yjlee168 2010-04-26 08:16
        
        NCA → Statistical analysis for parallel study Helmut 2010-04-26 13:12
        
        NCA → Statistical analysis for parallel study yjlee168 2010-04-26 18:43
        
        dilemma yjlee168 2010-04-26 08:41
        Equal variances d_labes 2010-04-26 09:04
        
        Equal variances yjlee168 2010-04-26 09:22
        
        GLM = Equal variances d_labes 2010-04-26 13:29
        
        GLM = Equal variances Helmut 2010-04-26 14:45
        
        I'm a believer d_labes 2010-04-26 15:58
        
        I'm a believer Helmut 2010-04-26 16:31
        
        Equal variances Helmut 2010-04-26 12:55
        
        gls() for unequal variances?d_labes 2010-04-26 16:36
        
        gls() for unequal variances? Helmut 2010-04-26 17:00
        Sims Helmut 2010-04-27 01:36
        
        Sandwich - Simsalabim d_labes 2010-04-28 10:58
        
        Sandwich - Simsalabim Helmut 2010-04-28 14:19
        parametrization of R function rlnorm martin 2010-05-02 18:22
        
        Mean of log-normal d_labes 2010-05-03 16:22
        parametrization of R function rlnorm ElMaestro 2013-07-26 21:42
        
        Martin‽ Helmut 2013-07-28 02:01