RE: [EXTERNAL] RE: Statistical power computation based on the wald test

Hello all: I would just like to add some information to help the discussion along. In addition to the variance-covariance matrix that is outputted in the .cov file that Ken mentioned, the Fisher information matrix itself (inverse of variance-covariance) is also outputted in the .coi file. Additional files, such as .rmt (R matrix), and .smt (S matrix) are also outputted upon user request ($COV PRINT=RS, for example) A test related to Wald and log-likelihood ratio tests is the Lagrange Multiplier test. For this purpose, NONMEM outputs the following in the .ext file: Iteration -1000000008 lists the partial derivative of the log likelihood (-1/2 OFV) with respect to each estimated parameter. PFIM, POPED, and NONMEM's $DESIGN calculate the expected FIM with respect to the data, and the expected value R matrix is equivalent to the expected value of the S matrix. That is, Ey(R)= Ey(S). Several companion/interface software to NONMEM have additional model evaluation facilities, such as stepwise covariate model (scm) building in Perl Speaks NONMEM, and Wald test in PDxPop. Robert J. Bauer, Ph.D. Senior Director Pharmacometrics R&D ICON Early Phase 820 W. Diamond Avenue Suite 100 Gaithersburg, MD 20878 Office: (215) 616-6428 Mobile: (925) 286-0769 [email protected]<mailto:[email protected]> http://www.iconplc.com