See my responses in brackets below.
- Original Message -
From: Rolf Turner
To: Scott Raynaud
Cc: "r-help@r-project.org"
Sent: Wednesday, November 16, 2011 6:04 PM
Subject: Re: [R] package installtion
On 17/11/11 05:37, Scott Raynaud wrote:
> That might be an option if
al Message -
> From: Rolf Turner
> To: Scott Raynaud
> Cc: "r-help@r-project.org"
> Sent: Wednesday, November 16, 2011 6:04 PM
> Subject: Re: [R] package installtion
>
> On 17/11/11 05:37, Scott Raynaud wrote:
>> That might be an option if it were
aud
Cc: "r-help@r-project.org"
Sent: Wednesday, November 16, 2011 6:04 PM
Subject: Re: [R] package installtion
On 17/11/11 05:37, Scott Raynaud wrote:
> That might be an option if it weren't my most important predictor. I'm
> thinking my best bet is to use MLWin for
On 17/11/11 05:37, Scott Raynaud wrote:
That might be an option if it weren't my most important predictor. I'm
thinking my best bet is to use MLWin for the estimation since it will properly
set fixed effects
to 0. All my other sample size simulation programs use SAS PROC IML which I
don't
MLWin sets the associated fixed
effects to 0. When R choked, I increased from 20 to 60 as my minimum as
suggested in the MLPowSim documentation. Still no luck.
- Original Message -
From: Uwe Ligges
To: r-help@r-project.org
Cc: Scott Raynaud
Sent: Wednesday, November 16, 2011 1:01
Ligges
- Original Message -
From: Uwe Ligges
To: Scott Raynaud
Cc: "r-help@r-project.org"
Sent: Wednesday, November 16, 2011 9:48 AM
Subject: Re: [R] package installtion
On 16.11.2011 16:08, Scott Raynaud wrote:
All right. I upped my level 2 sampl
I like R since it's free, but I can't work around the
problem
I'm currently having.
- Original Message -
From: Uwe Ligges
To: Scott Raynaud
Cc: "r-help@r-project.org"
Sent: Wednesday, November 16, 2011 9:48 AM
Subject: Re: [R] package installtion
On 16.11
ere's a
way to do this.
Why don't you simply delete that variable and hence don't estimate
coefficients for it
Uwe Ligges
- Forwarded Message -
From: Scott Raynaud
To: "r-help@r-project.org"
Cc:
Sent: Wednesday, November 16, 2011 7:28 AM
Subject: Re: [R]
d Message -
From: Scott Raynaud
To: "r-help@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
an be done. I've looked at the
documentation but it's still not clear.
- Original Message -
From: Uwe Ligges
To: Scott Raynaud
Cc: "r-help@r-project.org"
Sent: Wednesday, November 16, 2011 2:44 AM
Subject: Re: [R] package installtion
On 15.11.2011 21:34, Scott Rayn
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.
OK, I think I see the problem. Rather than setting method="nAGQ" I need
nAGQ=1. Doing so throws the following error:
"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 evaluat
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 av
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.
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