[R-sig-ME] GLMMs with Adaptive Gaussian Quadrature - GLMMadaptive 0.5-1
d@r|zopou|o@ @end|ng |rom er@@mu@mc@n|
Wed Jan 30 14:00:48 CET 2019
Dear R mixed-model users,
A new version of GLMMadaptive (0.5-1) has been rolled out on CRAN.
Summary: GLMMadaptive fits mixed effects models using adaptive
Gaussian quadrature to approximate the integrals over the random
effects, allowing also for user-specified models.
- Support is provided for the **effects** and **ggeffects** packages for
producing effect plots.
- Support is provided for the **DHARMa** package for checking the
goodness-of-fit of fitted mixed models using scaled simulated residuals.
Examples can be found in: vignette("Goodness_of_Fit", package =
- Function marginal_coefs() for calculating coefficients with a marginal
/ population-averaged interpretation has a faster implementation.
- The optimizer nlminb() can now also be invoked using the new control
argument 'optimizer'; a new vignette describes how to control the
optimization and numerical integration procedures in the package:
vignette("Optimization", package = "GLMMadaptive")
- New family object students.t() for fitting (robust) linear mixed
models with a Student's t distribution for the error terms.
As always, any kind of feedback is more than welcome.
Professor of Biostatistics
Department of Biostatistics
Erasmus University Medical Center
Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands
Web (personal): http://www.drizopoulos.com/
Web (work): http://www.erasmusmc.nl/biostatistiek/
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