RE: Question: Number of ETA and EPS in statistic significance

From: "Piotrovskij, Vladimir [JanBe]" <VPIOTROV@janbe.jnj.com> Subject: RE: Question: Number of ETA and EPS in statistic significance Date: Thu, 27 May 1999 09:16:47 +0200 Dear Takeshi, As the matter of fact, we can only very roughly evaluate statistical significance of changes in minimum objective function value (MOF). If we fit two nested models, and one of them is a reduced version of the other, the difference in MOF being the difference in -2*max(LogLik) is asymthotically Chi-squared distributed with q degrees of freedom where q is the number of skipped parameters (normally one). Only with the number of observations tend to infinity the corresponding P-values are correct, and the difference of 3.84 can be considered as significant (P<0.05). In any real situation it is always preferable to apply more conservative tests: 6.6 (P<0.01) or even 7.9 (P<0.005). The situation with random effect parameters, as mentioned by Mats, is much more complicated. In any case, the inclusion of random effects for structural parameters in the model should reduce the residual (unexplained) variability in the dependent variable, and I would suggest this as one of the most important model selection criterion. Best regards, Vladimir Vladimir Piotrovsky, PhD Clinical Pharmacokinetics, ext 5463 Janssen Research Foundation 2340 Beerse, Belgium e-mail: vpiotrov@janbe.jnj.com