## Hidden features of WNL Bioequivalence [Software]

Hi ElMaestro et al.,

In WNL you have only one module which is MIXED by default.

But what about RANDOM statements inside PROC GLM (remember the usual FDA SAS code for sinple 2X2 crossover)?

See the guide:

But is it MIXED or GLM+RANDOM?

Later:

Here ya go! This is GLM with RANDOM!

That's important hidden feature:

- the design (replicate/non-replicate) is caught on the fly,

- for 2X2 bioequivalence fixed(Sequence + Formulation + Period), Subject as Random mean GLM+RANDOM,

- for replicated designs the default model is the model proposed by FDA (also EMA Method C):

And you need to manually change the model to use EMA ABEL (Method A or B)

- for replicated designs fixed(Sequence + Formulation + Period) and Subject as Random mean MIXED model (and you don't get SS, DFs could be floats). This is EMA Method B.

- To switch to ANOVA with replicated designs you need to manually move subject to fixed terms tab and remove everything from Random Tab.

PS: all these things Simon and other trainers are explaining during training sessions

❝ In a 222BE trial the result is generally produced with a linear model, not a mixed model, regardless of authority. In that situation the whole concept of denominator df's if irrelevant. The residual df's will be an integer.

❝ So, I am guessing you fit your model with subject as random, and hence it becomes a mixed model.

In WNL you have only one module which is MIXED by default.

But what about RANDOM statements inside PROC GLM (remember the usual FDA SAS code for sinple 2X2 crossover)?

See the guide:

`Fixed effects model: Sequence + Formulation + Period`

– Unless the bioequivalence preference Default for 2x2 crossover set to all fixed effects is turned on in the Preferences dialog (Edit > Preferences > LinMixBioequivalence), in which case the model is Sequence + Subject(Sequence) + Formulation + Period.

Random effects model: Subject(Sequence) and Type: Variance Components

– Unless the bioequivalence preference Default for 2x2 crossover set to all fixed effects is turned on, in which case the model is not specified (the field is empty).

But is it MIXED or GLM+RANDOM?

Later:

`Since there is no repeated specification, the default error model ε ~ `*N*(0, σ^{2} *I*) is used. This is equivalent to the classical analysis method, but using maximum likelihood instead of method of moments to estimate inter-subject variance. Using Subject as a random effect this way, the correct standard errors will be computed for sequence means and tests of sequence effects.

Here ya go! This is GLM with RANDOM!

That's important hidden feature:

- the design (replicate/non-replicate) is caught on the fly,

- for 2X2 bioequivalence fixed(Sequence + Formulation + Period), Subject as Random mean GLM+RANDOM,

- for replicated designs the default model is the model proposed by FDA (also EMA Method C):

`Fixed effects model: Sequence + Formulation + Period`

Random effects model: Subject(Sequence) and Type: Variance Components

Repeated specification: Period

– Variance Blocking Variables: Subject

– Group: Treatment

– Type: Variance Components

And you need to manually change the model to use EMA ABEL (Method A or B)

- for replicated designs fixed(Sequence + Formulation + Period) and Subject as Random mean MIXED model (and you don't get SS, DFs could be floats). This is EMA Method B.

- To switch to ANOVA with replicated designs you need to manually move subject to fixed terms tab and remove everything from Random Tab.

PS: all these things Simon and other trainers are explaining during training sessions

—

Kind regards,

Mittyri

Kind regards,

Mittyri

### Complete thread:

- About the Partial SS in Boequivalence results in WinNonlin 8.1 fyy897854960 2018-11-01 09:28 [Software]
- About the Partial SS in Boequivalence results in WinNonlin 8.1 mittyri 2018-11-01 11:50
- About the Partial SS in Boequivalence results in WinNonlin 8.1 fyy897854960 2018-11-01 14:16

- About the Partial SS in Boequivalence results in WinNonlin 8.1 ElMaestro 2018-11-01 22:49
- RTFM Helmut 2018-11-01 23:12
- Hidden features of WNL Bioequivalencemittyri 2018-11-02 11:19

- About the Partial SS in Boequivalence results in WinNonlin 8.1 mittyri 2018-11-01 11:50