[R-sig-ME] Error message when handling complete separation

[Amal Dahounto]

Ok;
thank you so much for reply and your suggestion.
Regards,

Le lun. 21 oct. 2019 à 13:32, D. Rizopoulos <d.rizopoulos using erasmusmc.nl> a
écrit :

> In GLMMadaptive you can solve separation issues by including a penalty
> term for the coefficients. You may find an example on how to do this at the
> bottom of this vignette:
> https://drizopoulos.github.io/GLMMadaptive/articles/GLMMadaptive_basics.html
>
>
> Best,
> Dimitris
>
> *From: *C. AMAL D. GLELE <altessedac2 using gmail.com>
> *Date: *Monday, 21 Oct 2019, 13:21
> *To: *R SIG Mixed Models <r-sig-mixed-models using r-project.org>
> *Subject: *[R-sig-ME] Error message when handling complete separation
>
> Hi, all.
> When trying to handle a complete separation case
> ( initialmodel<-glmer(resp~treatment+(1|net),family=binomial,data=mydata) ,
> where: treatment is a factor with 4 levels; net has 4 levels;
> resp<-cbind(,)
> Warning message:
> unable to evaluate scaled gradient Hessian is numerically singular:
> parameters are not uniquely determined
> Outputs: huge estimates, huges sderror and p-value=1 everywhere
> )
> to solve this, I tried the following fit;
> mod2kisBW_unsep1<-
>
> bglmer(respkisBW~treatment+(1|net),data=conedata1kisBW,family=binomial,fixef.prior
> = normal(cov=diag(9,4)))
> but, I get the error message below:
>
> Error in length(value <- as.numeric(value)) == 1L :
>   pwrssUpdate did not converge in (maxit) iterations
>
> 1) what are the possible causes of such a problem?
> 2) how can I figure it out?
> Thanks, in advance.
> Regards,
>
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Amal DAHOUNTO GLELE C.



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