[R] package installtion

Scott Raynaud scott.raynaud at yahoo.com
Wed Nov 16 16:08:34 CET 2011


All right.  I upped my level 2 sample size to 60.  My log displays the following:

                 Simulation for sample sizes of  60  macro and unbalanced micro units
 Iteration remain= 990   
 Iteration remain= 980   
There were 27 warnings (use warnings() to see them)
Error in diag(vcov(fitmodel)) : 
  error in evaluating the argument 'x' in selecting a method for function 'diag': Error in asMethod(object) : matrix is not symmetric [1,2]

Looking at the warnings I see:

26: glm.fit: algorithm did not converge
27: In mer_finalize(ans) : gr cannot be computed at initial par (65)

The first 25 are like 26.  So, it seems I'm having the same problem as before.  Again, if this is due to a column of zeroes in my x matrix, the best solution would be to assign zeroes to the fixed effects, but I'm not sure if there's a way to do this.
 
----- Forwarded Message -----
From: Scott Raynaud <scott.raynaud at yahoo.com>
To: "r-help at r-project.org" <r-help at r-project.org>
Cc: 
Sent: Wednesday, November 16, 2011 7:28 AM
Subject: Re: [R] package installtion

Well, I could increase the sample size for my second level in hopes that my simulation would run correctly.  However, a better solution would be to assign values of 0 to the fixed effects for this pass through the simulation.  I'm such a novice with R that I don't know if that can be done.  I've looked at the documentation but it's still not clear.

 
----- Original Message -----
From: Uwe Ligges <ligges at statistik.tu-dortmund.de>
To: Scott Raynaud <scott.raynaud at yahoo.com>
Cc: "r-help at r-project.org" <r-help at r-project.org>
Sent: Wednesday, November 16, 2011 2:44 AM
Subject: Re: [R] package installtion



On 15.11.2011 21:34, Scott Raynaud wrote:
> OK, I think I see the problem.  Rather than setting method="nAGQ" I need nAGQ=1.  Doing so throws the following error:

Congratulations, now you understood what R meant with its message 
"Argument ‘method’ is deprecated."

> "Warning messages:
> 1: glm.fit: algorithm did not converge
> 2: In mer_finalize(ans) : gr cannot be computed at initial par (65)
> Error in diag(vcov(fitmodel)) :
>    error in evaluating the argument 'x' in selecting a method for function 'diag': Error in asMethod(object) : matrix is not symmetric [1,2]"
>
> I need some help interpreting and debugging this.  One thing that I suspect is that there is a column of zeroes in the design matrix,

So have you not even tried to get rid of that? Oh, come on.

Uwe Ligges



> but I'm not sure.  Any other possibilities here and how can I diagnose?
>
> ----- Original Message -----
> From: Scott Raynaud<scott.raynaud at yahoo.com>
> To: "r-help at r-project.org"<r-help at r-project.org>
> Cc:
> Sent: Tuesday, November 15, 2011 2:11 PM
> Subject: Re: package installtion
>
> Never mind-I fixed it.
>
> My script is throwing the following error:
>
> "Error in glmer(formula = modelformula, data = data, family = binomial(link = logit),  :
>    Argument ‘method’ is deprecated.
> Use ‘nAGQ’ to choose AGQ.  PQL is not available."
>
> I remember hearing somewhere that PQL is no longer available on lme4 but I have AGQ specified.
>
> Here's the line that fits my model:
>
> (fitmodel<- lmer(modelformula,data,family=binomial(link=logit),method="AGQ"))
>
> If I change it to nAGQ I still get an error.
>
> Any ideas as to what's going on?
>
> ----- Original Message -----
> From: Scott Raynaud<scott.raynaud at yahoo.com>
> To: "r-help at r-project.org"<r-help at r-project.org>
> Cc:
> Sent: Tuesday, November 15, 2011 1:50 PM
> Subject: package installtion
>
> I'm getting the following error in a script: "Error: could not find function "lmer."    I'm wondering of my lme4 package is installed incorrectly.  Can someone tell me the installation procedure?  I looked at the support docs but couldn't translate that into anything that would work.
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.



More information about the R-help mailing list