[R-sig-ME] GLMMs with Adaptive Gaussian Quadrature - GLMMadaptive 0.2-0

[D. Rizopoulos]

Dear R mixed-model users,

A new version of GLMMadaptive (0.2-0) has been rolled out on CRAN.

Summary: GLMMadaptive can fit mixed effects models using adaptive 
Gaussian quadrature to approximate the integrals over the random 
effects, allowing also for user-specified models.

New features:

- Zero-inflated Poisson and negative binomial models are now implemented 
using the family objects zi.poisson() and zi.negative.binomial(), 
respectively. In addition, taking into advantage of the fact that users 
can specify their own log density functions for the outcome, two-part / 
hurdle model can also be implemented. For examples, check the vignette: 
https://goo.gl/PkpTr4

- The predict() method is now fully available. It calculates 
predictions, and standard errors for models returned by mixed_model() at 
three levels:

   o "mean subject": only the fixed effects part corresponding to 
predictions for the average subject (but not population averaged 
predictions in case of nonlinear link functions).

   o "marginal": predictions using the marginalized coefficients that 
correspond to population averaged predictions.

   o "subject specific": predictions at the subject level. These can be 
also calculated for subjects not originally in the dataset (i.e., 
estimates of the random effects are internally obtained).

- The simulate() method is available to simulate data from fitted mixed 
models. This can be used for instance to perform replication / posterior 
predictive checks. More info in the vignette: https://goo.gl/nKK8kt

As always, any kind of feedback is more than welcome.

Best,
Dimitris


-- 
Dimitris Rizopoulos
Professor of Biostatistics
Department of Biostatistics
Erasmus University Medical Center

Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands
Tel: +31/(0)10/7043478
Fax: +31/(0)10/7043014
Web (personal): http://www.drizopoulos.com/
Web (work): http://www.erasmusmc.nl/biostatistiek/
Blog: http://iprogn.blogspot.nl/