Intersubject variation in replicated BE study [General Sta­tis­tics]

posted by atish_azad – 2008-03-31 17:02 (6651 d 00:23 ago) – Posting: # 1731
Views: 14,771

Dear d_labes,

Thank you for the reply, I need inter-subject variation because it is written in the protocol.
After refering to the mail given to Andrew by Dave and GSK BDS Technical Report 2002 - 01, I found the answer to the question.

❝ The replicate SAS output gives all of the information needed to calculate

❝ intra- and inter-CV, in it outputs of covariate matrix ("Covariate

❝ Parameter Estimates"). The SAS output look like this:


❝ Covariate Parameter Estimates

❝ Cov Parm Subject Group Estimate

❝ FA(1,1) Subject 0.4289 <---- (sig_BR, the between-subject standard

❝ deviation for the Reference product)

❝ FA(2,1) Subject 0.3131 <---- (sig_BT, the between-subject standard

❝ deviation for the Test product)

❝ FA(2,2) Subject <---- (sig_D, the subject-by-formulation interaction

❝ term)

❝ Residual Subject Formulation R 0.1479 <---- (sig_WR^2, the within-subject

❝ standard deviation for the Reference product)

❝ Residual Subject Formulation T 0.2539 <---- (sig_WT^2, the within-subject

❝ standard deviation for the Test product)


❝ The intra-subject variabilities are still calculated from the residuals as

❝ in a 2-way crossover, using:

❝ IntraCV_R = 100%*sqrt(exp(sig_WT^2)-1) (in this case, =

❝ 100*sqrt(exp(0.1479)-1) = 39.92%

❝ IntraCV_T = 100%*sqrt(exp(sig_WR^2)-1) (in this case, =

❝ 100*sqrt(exp(0.2539)-1) = 53.76%


❝ FA(1,1) and FA(2,1) are the inter-subject standard deviations for Reference

❝ and Test products, respectively:

❝ InterCV_R = 100%*sqrt(exp(sig_BT^2)-1) = 100*sqrt(exp(0.4289^2)-1) = 44.94%

❝ InterCV_T = 100%*sqrt(exp(sig_BR^2)-1) = 100*sqrt(exp(0.3131^2)-1) = 32.09%


Kindly let me know whether the above calculate inter and intra subject variability are correct.

In SAS code the Random statement, TYPE=FA0(2) if replaced by TYPE=CSH we could directly get inter and intra subject variance, isn't it?

Regards,

Atish

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