Calculation of intra-subject CVs in replicate design [General Sta­tis­tics]

posted by ddubins  – Toronto, 2008-03-01 20:28 (5947 d 15:11 ago) – Posting: # 1652
Views: 16,659

Hi Andrew,

It's a bit late for this reply, but I found the answer to your question. You don't need to run proc GLM. The replicate SAS output gives all of the information you need to calculate intra- and inter-CV, where it outputs the covariate matrix ("Covariate Parameter Estimates"). The SAS output might look like this:

Covariate Parameter Estimates
Cov Parm Subject Group Estimate
FA(1,1) Subject 0.5928 <---- (sig_BT, the between-subject standard deviation for the Test product)
FA(2,1) Subject 0.4968 <---- (sig_BR, the between-subject standard deviation for the Reference product)
FA(2,2) Subject 2E-17 <---- (sig_D, the subject-by-formulation interaction term)
Residual Subject Treatment A 0.124 <---- (sig_WT^2, the within-subject standard deviation for the Test product)
Residual Subject Treatment B 0.242 <---- (sig_WR^2, the within-subject standard deviation for the Reference product)

The intra-subject variabilities are still calculated from the residuals as in a 2-way crossover, using:
IntraCV_T = 100%*sqrt(exp(sig_WT^2)-1) (in this case, = 100*sqrt(exp(0.124)-1) = 36.3%
IntraCV_R = 100%*sqrt(exp(sig_WR^2)-1) (in this case, = 100*sqrt(exp(0.242)-1) = 52.3%

FA(1,1) and FA(2,1) are the inter-subject standard deviations for Test and Reference products, respectively:
InterCV_T = 100%*sqrt(exp(sig_BT^2)-1) = 100*sqrt(exp(0.5928^2)-1) = 64.9%
IntraCV_R = 100%*sqrt(exp(sig_BR^2)-1) = 100*sqrt(exp(0.4968^2)-1) = 52.9%

Hope this helps,
Dave

David Dubins, Ph.D., B.A.Sc.
Associate Professor, Teaching Stream
Director, Pharmaceutical Chemistry Specialist Program
Leslie Dan Faculty of Pharmacy
University of Toronto

144 College Street (room PB802), Toronto, ON M5S 3M2
Tel. +1 416-946-5303; FAX: +1 416 978-8511

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