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RegisterEMA crippled approach [Software]
Dear John,
let me snap in.
If you aimed for an EMA submission you have to do some sort of that.
To cite the EMA guideline again (we had this already occasionally discussed here, also by yourself!):
"In studies with more than two treatment arms (e.g. a three period study including two references, one from EU and another from USA, or a four period study including test and reference in fed and fasted states), the analysis for each comparison should be conducted excluding the data from the treatments that are not relevant for the comparison in question."
Practically this means to me: Don't change anything in the dataset. Keep periods and sequences as they are. Only forgot 1/3 of your data per comparison under consideration.
I'm not a friend of this crippled approach
.
But ... On the other hand the full analysis is crucially depending on the assumption of a common error variance for the three treatments. What happens and what are the implications if this assumption is violated is not really clear to me.
Is the case of heteroscedastic variances in BE studies an issue? Don't ask me
. See a quote of Steven Senn here.
let me snap in.
❝ ... How? By collapsing the data into a 2-way study while preserving the order of the T and R treatments are per sequence (i.e., ABC → CB, BAC → AC, CBA → CA etc etc) and run stats? Or remove the 2nd formulation data completely and run stats? So that the width of the 90% CI is attributed to intrasubject CV from both 1st formulation and reference.
If you aimed for an EMA submission you have to do some sort of that.
To cite the EMA guideline again (we had this already occasionally discussed here, also by yourself!):
"In studies with more than two treatment arms (e.g. a three period study including two references, one from EU and another from USA, or a four period study including test and reference in fed and fasted states), the analysis for each comparison should be conducted excluding the data from the treatments that are not relevant for the comparison in question."
Practically this means to me: Don't change anything in the dataset. Keep periods and sequences as they are. Only forgot 1/3 of your data per comparison under consideration.
I'm not a friend of this crippled approach
. But ... On the other hand the full analysis is crucially depending on the assumption of a common error variance for the three treatments. What happens and what are the implications if this assumption is violated is not really clear to me.
Is the case of heteroscedastic variances in BE studies an issue? Don't ask me
. See a quote of Steven Senn here.—
Regards,
Detlew
Regards,
Detlew
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Ing. Helmut Schütz