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

[Dimitris Rizopoulos]

It�s also available in GLMMadaptive: https://drizopoulos.github.io/GLMMadaptive/articles/Custom_Models.html

________________________________
���: � ������� R-sig-mixed-models <r-sig-mixed-models-bounces using r-project.org> �� ������ ��� ������ Ben Bolker <bbolker using gmail.com>
��������: ���������, ����������� 9, 2024 23:11
����: r-sig-mixed-models using r-project.org <r-sig-mixed-models using r-project.org>
����: Re: [R-sig-ME] Distributional Assumption in lmer()



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   For what it's worth I think you can probably also do this in brms, if
you want to go down the Bayesian rabbit hole ...

On 2024-02-09 5:01 p.m., Hedyeh Ahmadi wrote:
> Thank you for the quick and informative reply.
>
> Best,
>
> Hedyeh Ahmadi, Ph.D.
> Statistician
> Keck School of Medicine
> Department of Preventive Medicine
> University of Southern California
>
> LinkedIn
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> ________________________________
> From: R-sig-mixed-models <r-sig-mixed-models-bounces using r-project.org> on behalf of Ben Bolker <bolkerb using mcmaster.ca>
> Sent: Friday, February 9, 2024 1:34 PM
> To: r-sig-mixed-models using r-project.org <r-sig-mixed-models using r-project.org>
> Subject: Re: [R-sig-ME] Distributional Assumption in lmer()
>
>     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
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