EMA catched on the bear way [Regulatives / Guidelines]
Dear all,
after studying the presentations of the EGA workshop I have catched the EMA on the bear way .
Just to cite from the Session 3 combined presentation, Slide 35:
"The guideline requests subject and subject within sequence as fixed effects – in practice this shouldn’t make much difference.
(As long as we talk about 2x2 cross-over and estimate of treatment effect. But wrong for the sequence effects test. D.L.)
Mixed effects modelling not considered absolutely necessary for replicate designs. Model with terms for sequence, subject (sequence), period and formulation still works for replicate design (no need to fit e.g. interaction term).
(Model the same as for a 2x2 cross-over, as implemented in bear but there via mixed model function lme(). Neglecting any SxF interaction. D.L.)
Intra-subject variability for reference can be estimated by removing test data from data-set and fitting model with sequence, subject (sequence) and period."
(Oops. Again an evaluation neglecting part of the data. Like that 3x3 cross-over story. D.L.)
Have a look at my "Adventures on the bear way" to see that this is again a case of adopting an anti-conservative statistical method. See Willavize et.al.
after studying the presentations of the EGA workshop I have catched the EMA on the bear way .
Just to cite from the Session 3 combined presentation, Slide 35:
"The guideline requests subject and subject within sequence as fixed effects – in practice this shouldn’t make much difference.
(As long as we talk about 2x2 cross-over and estimate of treatment effect. But wrong for the sequence effects test. D.L.)
Mixed effects modelling not considered absolutely necessary for replicate designs. Model with terms for sequence, subject (sequence), period and formulation still works for replicate design (no need to fit e.g. interaction term).
(Model the same as for a 2x2 cross-over, as implemented in bear but there via mixed model function lme(). Neglecting any SxF interaction. D.L.)
Intra-subject variability for reference can be estimated by removing test data from data-set and fitting model with sequence, subject (sequence) and period."
(Oops. Again an evaluation neglecting part of the data. Like that 3x3 cross-over story. D.L.)
Have a look at my "Adventures on the bear way" to see that this is again a case of adopting an anti-conservative statistical method. See Willavize et.al.
—
Regards,
Detlew
Regards,
Detlew
Complete thread:
- EMA catched on the bear wayd_labes 2010-06-16 15:14 [Regulatives / Guidelines]