This is hopeless, since you never seem to listen to our advice,
therefore this will be my very last try:
So you actually need local advice, both for statistical concepts and R
related. No statistics software can estimate effects of variables that
you observed to be constant (e.g. 0) all the time. If any software does,
please delete it a once from your machine.
Instead, ask a local statistician for advice on your problem. You
certainly want to show the data and your model to the local expert -
since you don't show us. And then you want to ask for local R course
since reading the documentation seems not to help. Applying mtrace() in
a non exiting object shows this straight away.
Uwe Ligges
On 17.11.2011 15:49, Scott Raynaud wrote:
I believe the problem is a column of zeroes in my x matrix. I have tried the
suggestions in the documentation,
so now to try to confirm the probelm I'd like to run debug. Here's where I
think the problem is:
###~~~~~~~~~~ Fitting the model using lmer funtion ~~~~~~~~~~###
(fitmodel<- lmer(modelformula,data,family=binomial(link=logit),nAGQ=1))
mtrace(fitmodel)
I added the mtrace to catch the error, but get the following:
Error in mtrace(fitmodel) : Can't find fitmodel
How can I debug this?
----- Original Message -----
From: Rolf Turner<rolf.tur...@xtra.co.nz>
To: Scott Raynaud<scott.rayn...@yahoo.com>
Cc: "r-help@r-project.org"<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 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 have/can't afford. I like R since it's free, but I can't work around the
problem
I'm currently having.
This is the ``push every possible button until you get a result and to hell
with what
anything actually means'' approach to statistics. The probability of getting a
*meaningful* result from this approach is close to zero.
Why don't you try to *understand* what is going on, rather than wildly throwing
every possible piece of software at the problem until one such piece runs?
cheers,
Rolf Turner
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