| NEWS | R Documentation |
The vignettes should now appear as pdf files on CRAN.
The method used to determine the rank of a matrix was brought into agreement with the base package when the matrix was a base matrix. Prior to this it was possible to get an error from a call to mix that should have returned. Now these calls to mix should return. Thanks to Christian Kjeldsen of Aarhus University, Danish School of Education, for pointing this issue out.
The Wald test now works for generalized linear models instead of throwing an error. Thanks to Christian Kjeldsen for pointing this issue out as well.
WeMix can now accept conditional weights. See the cWeights argument in the mix function.
the mix function checks weights and writes a message if they may be conditional and cWeights is set to FALSE.
Linear model evaluation is more robust and can handle data with non-invertible Z matrixes within a group.
Linear models now use base::qr more aggressively because of poor performance of the Matrix::qr.coef function on a sparse QR when the system is singular. This previously resulted in very large variance estimates. This also fixed an invalid 'times' argument error.
The code in the vignette was not the code used to generate the results and some values were incorrectly entered in the comparison table under the mix column. These problems were fixed.
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.