[R-sig-ME] Random Effect Tobit

[Ben Bolker]

This CrossValidated answer: 
https://stats.stackexchange.com/questions/544511/zero-inflated-gaussian-for-weights-below-zero-recorded-as-0?noredirect=1#comment999636_544511

  says that the censReg package can handle random effects Tobit models 
via Gauss-Hermite Quadrature (GLMMadaptive is great, but it's nice to 
have options)

On 9/14/21 3:32 AM, Dimitris Rizopoulos wrote:
> You can use the GLMMadaptive package (https://drizopoulos.github.io/GLMMadaptive/) and the censored.normal() family object. An example is given here: https://drizopoulos.github.io/JMbayes2/articles/Non_Gaussian_Mixed_Models.html#censored-linear-mixed-models-1
> 
> 
> Best,
> Dimitris
> 
> -----Original Message-----
> From: R-sig-mixed-models <r-sig-mixed-models-bounces using r-project.org> On Behalf Of Hedyeh Ahmadi
> Sent: Tuesday, September 14, 2021 12:25 AM
> To: r-sig-mixed-models using r-project.org
> Subject: [R-sig-ME] Random Effect Tobit
> 
> Hello all,
> I was wonder if anyone is aware of an R package with random effect Tobit. Any help would be greatly appreciated.
> 
> Best,
> 
> Hedyeh Ahmadi, Ph.D.
> Statistician
> Keck School of Medicine
> Department of Preventive Medicine
> University of Southern California
> 
> Postdoctoral Scholar
> Institute for Interdisciplinary Salivary Bioscience Research (IISBR) University of California, Irvine
> 
> LinkedIn
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-- 
Dr. Benjamin Bolker
Professor, Mathematics & Statistics and Biology, McMaster University
Director, School of Computational Science and Engineering
Graduate chair, Mathematics & Statistics