Their ability to restrict the number of included parameter-covariate relationships while maintaining the predictive performance of the model was demonstrated using the antiarrythmic drug dofetilide. Criteria based on clinical relevance were found to be useful components in automated stepwise covariate model building.
Perl nonmem purge bootstrap files software#
The appropriateness of the methods and the consistency of the software tools were evaluated using a large selection of clinical and nonclinical data. The thesis describes the implementation of a set of statistical methods (the bootstrap, jackknife, case-deletion diagnostics, log-likelihood profiling and stepwise covariate model building), made available as tools through the software Perl-speaks-NONMEM (PsN). This involved the development of suitable software tools that allows for efficient use of these methods, characterisation of basic properties and demonstration of their usefulness when applied to real world data. The aim of this thesis was to facilitate the practical use of available and new statistical methods in the area of pharmacometric data analysis. The availability of software implementing modern statistical methods is important for efficient model building and evaluation throughout pharmacometric data analyses. Pharmacometrics uses models based on pharmacology, physiology and disease for quantitative analysis of interactions between drugs and patients. 2006 (English) Doctoral thesis, comprehensive summary (Other academic) Abstract
0 kommentar(er)
