Title | SNP_NLMM: Implement a flexible random effects density for generalized linear and nonlinear mixed models (SAS). |
Publication Type | Software |
Year of Publication | 2014 |
Authors | Vock, David M., Marie Davidian, and Anastasios A. Tsiatis |
Abstract | A SAS macro that overcomes the computational challenges to fit GLMMs and NLMMs where the random effects are assumed to follow a smooth density that can be represented by the seminonparametric formulation proposed by Gallant and Nychka (1987). The macro is flexible enough to allow for any density of the response conditional on the random eects and any nonlinear mean trajectory. |
Original Publication | SNP_NLMM: Implement a flexible random effects density for generalized linear and nonlinear mixed models (SAS). |
Project:
Software Weblinks: