Least square mean calculation for the fully replicate design [General Statistics]
❝ One question for the least square mean calculation for the fully replicate design as per USFDA in SAS.
❝ Please share your thoughts …
I think when changes for one value have been done - it was not changes only for formulation, it was changes for sequence and period also. And if you look at model coefficients probably you will find changes in sequence coefficient. estimate is calculated as L*β where L is a vector of known constants. For example if we have 2 sequence, 2 period, 2 formulation, length of β vector is 4 and for one formulation L = [1; 1/2; 1/2; 0] for other L = [1; 1/2; 1/2; 1]. When value changed its lead to changes in sequence part of β, and then to marginal value of each formulation.
I imagine it like this: one part of change is go to current formulation mean value, and some part goes to sequence and period (because it one model), and because sequence is crossed with other formulation it affect on other formulation level.
Edit: Unnecessary quote removed. Please delete everything from the text of the original poster which is not necessary in understanding your answer; see also this post #5! [Mittyri]
- Least square mean calculation for the fully replicate design Jaimik Patel 2019-10-31 11:19 [General Statistics]
- Very, very strange! Helmut 2019-10-31 14:36
- Inner workings of REML ElMaestro 2019-10-31 19:48
- Least square mean calculation for the fully replicate designPharmCat 2019-11-03 00:46