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.
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