| NEWS | R Documentation |
Linear models are now solved using an analytical solution based on work by Bates and Pinheiro, (1998). This solution is significantly faster than the previous adaptive quadrature method.
Non-linear models are still evaluated using adaptive quadrature.
WeMix can now fit weighted three-level linear models, see the Weighted Linear Mixed-Effects Model vignette for details. Non-linear models are still evaluated using adaptive quadrature and are limited to two-level models.
Model evaluation is now possible using Wald tests. Wald tests allow users to test both fixed effects and random effects variances.
Supports binomial models
Added ability to perform group and grand mean centering to increase comparability with Hierarchical Linear and Nonlinear Modeling (HLM) software
Although three-level models are not currently supported, in version 2.0.0, changes were made to the way groups handled and to the data structures used for integration over random effects so as to be compatible with the future development of three-level models.
Corrected the warning message for the fast option (using Rcpp)
fast option in mix defaults to FALSE now to prioritize accuracy over speed.