[R-sig-ME] How to specify user-defined matrix Z?
Zhengyang Zhou
Zhengyang.Zhou at UTSouthwestern.edu
Fri Sep 29 21:51:54 CEST 2017
Hi Jacob,
Thank you for your reply. I need to use lme4 because I want to test for the fixed effects (ie., beta), and the packages which can do it (eg, pbkrtest) is based on lme4.
Sincerely,
Zhengyang
________________________________________
From: R-sig-mixed-models <r-sig-mixed-models-bounces at r-project.org> on behalf of Jacob Bergstedt <jacoba at control.lth.se>
Sent: Friday, September 29, 2017 6:39 AM
To: r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] How to specify user-defined matrix Z?
Hi,
You can use the lmekin function in the coxme package.
Best regards,
Jacob
On 2017-09-29 12:28, Crump, Ron wrote:
> Hi Zhengyang,
>
>> In genetic studies, we sometimes include the genetic relatedness matrix as a variance component, so we have this following model:
>> Y~Xbeta+Zb+error,
>>
>> where beta are the fixed effects, b~N(0,sigma^2*I) are the random effects, error are the random error, Z is the cholesky decomposition of the known genetic relatedness matrix. So how to use lme4 to fit this model if we know X and Z beforehand? I can use the package "nlme" to do it using the code like
>>
>> lme(y~-1+X, random=list(group=pdIdent(~-1+Z))),
>> but how to do it using lme4?
> I think, assuming you are using I to indicate an identity matrix, that
> in neither case are you specifying a genetic relationship matrix, unless
> you are somehow incorporating it into Z (in which case I'd like to see how).
>
> I don't believe that either lme4 or nlme will allow you to do what you
> want. (Somebody might correct me on this).
>
> Within R you could certainly use MCMCglmm or INLA to do analysis of
> quantitative genetics data to obtain genetic parameters (or the asremlr
> interface to ASREML). I've not used it, but the pedigreemm package also
> looks like it would help you and there may be others. Outside of R,
> Karin Meyer's wombat program will also do the job.
>
>
> Regards,
> Ron.
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