[R-sig-ME] Distributional Assumption in lmer()

[Ben Bolker]

   No, but:

(1) glmmTMB has this (family = t_family)
(2) you can achieve a similar goal with the robustlmm package

   cheers
    Ben Bolker


On 2024-02-09 3:42 p.m., Hedyeh Ahmadi wrote:
> Hello All,
> I was wondering if there is a way to implement t-distribution assumption instead of family ="Gaussian" assumption in the lmer() function.
> 
> I am asking since I have been seeing heavy tails in my outcomes and it shows up in my residual diagnostic QQplot hence I think a t-distribution would be more appropriate compared to Normal distribution.
> 
> Any help would be greatly appreciated.
> 
> Best,
> 
> Hedyeh Ahmadi, Ph.D.
> Statistician
> Keck School of Medicine
> Department of Preventive Medicine
> University of Southern California
> 
> LinkedIn
> www.linkedin.com/in/hedyeh-ahmadi<http://www.linkedin.com/in/hedyeh-ahmadi>
> 
> 
> 
> 
> 
> 	[[alternative HTML version deleted]]
> 
> _______________________________________________
> R-sig-mixed-models using r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

-- 
Dr. Benjamin Bolker
Professor, Mathematics & Statistics and Biology, McMaster University
Director, School of Computational Science and Engineering
  Associate chair (graduate, math), Mathematics & Statistics
   > E-mail is sent at my convenience; I don't expect replies outside of
working hours.