Quite agree. Should have added this sort of detail.

2008/7/8 Robert Kushler <kushler@oakland.edu>:

>
> I'll add 2 cents worth here:  I have long advocated subtracting off a nice
> round number near the middle of the range of x values, rather than using
> the
> mean of the x values in the current data set.  This has a number of
> advantages,
> including ease of interpretation and the ability of others to easily
> reproduce
> the results and/or generate predicted values from the fitted model.  The
> same
> argument applies to rescaling data by e.g. shifting the decimal point
> rather
> than "standardizing" x.
>
> Regards,    Rob Kushler
>
>
>
> Gillian Raab wrote:
>
>> Very basic statistical principal. It reduces the correlation between the x
>> variables especially when you have quadratic terms. Models with correlated
>> covariates are ill conditioned and fit badly and are subject to rounding
>> errors.
>>
>> Those of us old enough to have to have done regressions with calculators
>> know this very well but you young folk don't seem to know about it. Give
>> it
>> a try and see if it helps.
>>
>> Gillian
>>
>> 2008/7/8 <yufeng@nsm.umass.edu>:
>>
>>  Thank for your suggestions but why u want to center x variables around
>>> zero
>>> in
>>> that way? I just don't understand what is the advantage by doing that.
>>>
>>> Yufeng
>>>
>>> Quoting Gillian Raab <gillian.raab@googlemail.com>:
>>>
>>>  2008/7/8 <yufeng@nsm.umass.edu>:
>>>>
>>>>  Please see below:
>>>>>
>>>>>  1) What version of lmer are you running? The new version post 23/6/08
>>>>>>
>>>>> copes
>>>>>
>>>>>> with difficult likelihoods better.
>>>>>>
>>>>> I used the most up-to-date version.
>>>>>
>>>>>  2) Have you changed anything in the elements of the control
>>>>>>
>>>>> parameter.
>>>
>>>> The
>>>>>
>>>>>> pre 23/6 verion had several parameters and the later one fewer. In
>>>>>> particular you can increase the iterations
>>>>>>
>>>>> How could I increase the iterations?
>>>>>
>>>> READ THE HELP FILE UNDER LMER AND THE CONTROL  PARAMETER
>>>>
>>>>
>>>>>  3) Have you centred your x variables so they have means around zero.
>>>>>>
>>>>> If
>>>
>>>> not
>>>>>
>>>>>> you should always do this as it will make the fitting easier
>>>>>>
>>>>> especially
>>>
>>>> with
>>>>>
>>>>>> quadratic terms. This ought to have been my first suggestion.
>>>>>>
>>>>> Do u mean the random effects of x's should be centered around 0? I
>>>>>
>>>> didn't
>>>
>>>> do
>>>>> that and I don't know how to do that in R? Could U tell me how? Thanks!
>>>>>
>>>> NOTHING FANCY JUST CALCULATE NEW X VARIABLES BY SUBTRACTING THE MEAN
>>>>
>>> VALUES
>>>
>>>>
>>>>>
>>>>>
>>>>>  4) Having another look at your model you say it is non-linear, but it
>>>>>>
>>>>> looks
>>>>>
>>>>>> linear to me if you set the squared terms as covariates too.
>>>>>>
>>>>> You are right the model should be linear.
>>>>>
>>>>>  Good luck
>>>>>>
>>>>>> Gillian Raab
>>>>>> Edinburgh
>>>>>>
>>>>>> On 03/07/2008, yufeng@nsm.umass.edu <yufeng@nsm.umass.edu> wrote:
>>>>>>
>>>>>>> Dear R-user,
>>>>>>>
>>>>>>> I am trying to use the R "lmer" function in lme4 package to fit a
>>>>>>>
>>>>>> non
>>>
>>>> linear
>>>>>>> mixed effects model. The model I wand to fit is at an individual
>>>>>>>
>>>>>> level
>>>
>>>> with
>>>>>
>>>>>> 4
>>>>>>> parameters. For all parameters both fixed and random effects have
>>>>>>>
>>>>>> to be
>>>
>>>> estimated, as well as their covariance matrix (see the formula
>>>>>>>
>>>>>> bellow).
>>>
>>>> y~x1+x1^2+x2+x2^2.
>>>>>>>
>>>>>>>
>>>>>>> I tried to fit the model with my data sets, but most of the time, R
>>>>>>>
>>>>>> returns
>>>>>
>>>>>> an
>>>>>>> error message.
>>>>>>> there are three main types of errors :
>>>>>>>
>>>>>>> - In mer_finalize(ans, verbose) :
>>>>>>>  function evaluation limit reached without convergence (9)
>>>>>>>
>>>>>>> -  there are false convergence (8)
>>>>>>>
>>>>>>> -there are singular convergence (7)
>>>>>>>
>>>>>>> Do you know how to resolve these problems. Is there a way to modify
>>>>>>>
>>>>>> the
>>>
>>>> parameters of the maximization algorithm to avoid these error
>>>>>>>
>>>>>> messages?
>>>
>>>> Thank you for your help and answers.
>>>>>>>
>>>>>>> Regards,
>>>>>>>
>>>>>>> Yufeng Zhang
>>>>>>>
>>>>>>> _______________________________________________
>>>>>>> R-sig-mixed-models@r-project.org mailing list
>>>>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>>>>>>
>>>>>>>
>>>>>>
>>>>>> --
>>>>>> Gillian M Raab
>>>>>> 10 Ainslie Place EH3 6AS
>>>>>> tel 0131 226 6234
>>>>>> mobile 07748 678 551
>>>>>>
>>>>>>
>>>>>
>>>>>
>>>>>
>>>> --
>>>> Gillian M Raab
>>>> 10 Ainslie Place EH3 6AS
>>>> tel 0131 226 6234
>>>> mobile 07748 678 551
>>>>
>>>>
>>>
>>>
>>>
>>
>>
>


-- 
Gillian M Raab
10 Ainslie Place EH3 6AS
tel 0131 226 6234
mobile 07748 678 551

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