NLMEM: a NEW SAS/IML macro for hierarchical nonlinear models

摘要: Analysis of longitudinal data is one the most challenging tasks in statistical modeling. In analysis, it often necessary to take into account nonlinear response a set parameters interest and correlation between measurements taken from same individual. addition, between- within-subject variation has be handled properly. An example addressing these issues hierarchical model, where parameter estimation can performed using linearization method. this paper new NLMEM SAS/IML macro for models proposed. The program uses portion code developed earlier NLINMIX. retains all benefits NLINMIX while allowing systematic part model structure specified IML syntax. Consequently, allows which are not tractable particular, us address advanced population pharmacokinetics pharmacodynamics by ordinary differential equations.