Bioequivalence and Bioavailability Forum

lme() answer and beyond ... [General Statistics]

posted by Helmut – Vienna, Austria, 2010-07-14 15:47 (5420 d 11:31 ago) – Posting: # 5624
Views: 14,183

Dear D. Labes,

let's continue!

           -2 REML log(LikH)   AIC       BIC

SAS (FDA)      272.910          ?         ?

PHX/WNL        251.724       273.724   304.923

lme()          271.654       291.654   320.096

❝ Seems WNL computes different.

Hhm; according to Phoenix 1.1 users' Guide:

Akaike's Information Criterion (AIC)
The Linear Mixed Effects object uses the smaller-is-better form of Akaike's Information Criterion:

AIC = –2L_R + 2s
where L_R is the restricted log-likelihood function evaluated at final fixed parameter estimates beta-hat and the final variance parameter estimates theta-hat, and s is the rank of the fixed effects design matrix X plus the number of parameters in theta (i.e., s = rank(X) + dim(theta)).
Schwarz's Bayesian Criterion (SBC)
The Linear Mixed Effects object uses the smaller-is-better form of Schwarz's Bayesian Criterion:

SBC = –2L_R + slog(N-r)
where L_R is the restricted log-likelihood function evaluated at the final estimates beta-hat and theta-hat,
N is the number of observations used,
r is the rank of the fixed effects design matrix X, and
s is the rank of the fixed effects design matrix X plus the number of parameters in theta
(i.e., s = rank(X) + dim(theta)).

                                                  Widened (EMA)

                      --- 90% CIs ---           acceptance range

            point est.  lower  upper    s²_WR      lower   upper

FDA (MoM)   0.8746     0.7216  1.0605  0.14332   0.7500  1.3334

SAS (FDA)   0.8632     0.7037  1.0498  0.1862    0.7204  1.3881

PHX/WNL     0.8632     0.7096  1.0500  0.18616   0.7204  1.3881

lme()       0.8628     0.7123  1.0452  0.18642   0.7203  1.3884

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

The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes

Complete thread:

SABE Reference Variability and CI Computation preyes323 2010-07-12 17:12 [General Statistics]
- Dataset Helmut 2010-07-12 17:26
  - Dataset preyes323 2010-07-12 18:20
    - Data format Helmut 2010-07-12 18:38
      - Data format preyes323 2010-07-13 01:16
        
        SAS and/or Phoenix/WinNonlin-experts around? Helmut 2010-07-13 02:29
        
        Phoenix/WinNonlin-experts around? d_labes 2010-07-13 12:15
        
        Phoenix/WinNonlin-experts around? Helmut 2010-07-13 13:42
        
        Mixed interest d_labes 2010-07-13 15:11
        
        Mixed interest Helmut 2010-07-13 19:19
        
        lme() answer and beyond ... d_labes 2010-07-14 10:41
        
        lme() answer and beyond ...Helmut 2010-07-14 13:47
        
        AIC, BIC and that all ... d_labes 2010-07-15 12:01
        
        To Err is Human d_labes 2010-07-13 11:51
        
        To Err is Human, but... Helmut 2010-07-13 13:45
        
        ... to Arr is Pirate d_labes 2010-07-13 15:47
        
        Brilliant page!!! ElMaestro 2010-07-14 21:03
        
        To Err is Human preyes323 2010-07-14 14:45
        
        Heads up! Helmut 2010-07-14 15:17
        To Err is Teacher d_labes 2010-07-15 11:05
        
        To Err is Human preyes323 2010-07-16 02:28
        
        To Err is Human d_labes 2010-07-16 10:42
        
        To Err is Human preyes323 2010-07-17 11:14
        
        Regulatory constants d_labes 2010-07-19 10:00
        
        Data format ElMaestro 2011-02-06 11:54
        
        SAS System Viewer Helmut 2011-02-06 13:02

lme() answer and beyond ... [General Sta­tis­tics]

Complete thread:

lme() answer and beyond ... [General Statistics]