[R] lme funcion in R

[David Winsemius]

On Aug 4, 2009, at 7:48 PM, Hongwei Dong wrote:

> Yeah, I have a very large sample size, about 60,000 observations.
> Multicollinearity should not be a problem here. The weird thing is  
> that SPSS
> can converge very quickly and gives out reasonable results.
> The only problem I can think of is that, my first level (random)  
> variables
> are dummy variables: 6 housing types, and I used five dummies in  
> model and
> one as the reference. I also tried to combine them into two groups  
> and use
> only dummy at random level, but it does not work either.
>
> is there any one here has similar experience with the LME function  
> in R?

I have absolutely no experience with "LME" but I can predict with very  
high probability that you would be getting more sensible result if you  
modeled those housing types with a single factor variable rather than  
creating 6 dummies. ((Would one generally not create a reference dummy?)

?factor

-- 
David.

>
> Thanks.
>
> Harry
>
>
>
> On Tue, Aug 4, 2009 at 1:28 AM, ONKELINX, Thierry
> <Thierry.ONKELINX at inbo.be>wrote:
>
>> Dear Harry,
>>
>> Your model seems rather complex. Do you have enough data to support  
>> it?
>> Did you check for multicollinearity between the variables?
>>
>> HTH,
>>
>> Thierry
>>
>>
>>
>> ------------------------------------------------------------------------
>> ----
>> ir. Thierry Onkelinx
>> Instituut voor natuur- en bosonderzoek / Research Institute for  
>> Nature
>> and Forest
>> Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
>> methodology and quality assurance
>> Gaverstraat 4
>> 9500 Geraardsbergen
>> Belgium
>> tel. + 32 54/436 185
>> Thierry.Onkelinx at inbo.be
>> www.inbo.be
>>
>> To call in the statistician after the experiment is done may be no  
>> more
>> than asking him to perform a post-mortem examination: he may be  
>> able to
>> say what the experiment died of.
>> ~ Sir Ronald Aylmer Fisher
>>
>> The plural of anecdote is not data.
>> ~ Roger Brinner
>>
>> The combination of some data and an aching desire for an answer  
>> does not
>> ensure that a reasonable answer can be extracted from a given body of
>> data.
>> ~ John Tukey
>>
>> -----Oorspronkelijk bericht-----
>> Van: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org 
>> ]
>> Namens Hongwei Dong
>> Verzonden: maandag 3 augustus 2009 19:45
>> Aan: r-help at r-project.org
>> Onderwerp: Re: [R] lme funcion in R
>>
>> Thanks for the replies above. Here are my script and data structure:
>> library(nlme)
>> tlevel<-lme(fixed = LN_unitlandval ~
>> MH_D+APT_D+ResOth_D+NonRes_D+Vacant_D+access_emp1+pct_vacant 
>> +transit_D+p
>> ark_dum,data=lusdrdata,random
>> = ~MH_D+APT_D+ResOth_D+NonRes_D+Vacant_D | TAZ)
>>
>> str:
>>
>> $ TAZ : int 100 100 100 100 100 100 100 100 100 100 ...
>> $ MH_D : num 0 0 0 0 0 0 0 0 0 0 ...
>> $ APT_D : num 0 0 0 0 0 0 0 0 0 0 ... $ ResOth_D : num 0 0 0 0 0 0  
>> 0 0 0
>> 0 ... $ NonRes_D : num 0 0 0 0 0 0 0 0 0 1 ...
>> $ Vacant_D : num 1 1 1 0 0 1 1 1 1 0 ...
>> $ access_emp1 : num 45.8 45.8 45.8 45.8 45.8 ...
>> $ pct_vacant : num 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 ... $
>> transit_D :
>> num 0 0 0 0 0 0 0 0 0 0 ... $ park_dum : num 0 0 0 0 0 0 0 0 0 0 ...
>>
>>
>> Thanks.
>>
>> Harry
>>
>>
>>
>> On Mon, Aug 3, 2009 at 10:36 AM, Jason Morgan <jwm-r-help at skepsi.net>
>> wrote:
>>
>>> On 2009.08.03 10:15:46, Hongwei Dong wrote:
>>>> Hi, R users,
>>>>  I'm using the "lme" function in R to estimate a 2 level mixed
>>>> effects model, in which the size of the subject groups are
>>>> different. It turned
>>> out
>>>> that It takes forever for R to converge. I also tried the same  
>>>> thing
>>
>>>> in
>>> SPSS
>>>> and SPSS can give the results out within 20 minutes. Anyone can  
>>>> give
>>
>>>> me
>>> some
>>>> advice on the lme function in R, especially why R does not  
>>>> converge?
>>> Thanks.
>>>>
>>>> Harry
>>>
>>> Hello Harry,
>>>
>>> As Chuck mentions, providing some more information on the model and
>>> the data you are using would be helpful. Also, be sure to compare  
>>> the
>>> optimization methods used in SPSS to that used in R. You can change
>>> the optimization method in R if the default seems to be causing
>>> issues. See help(lmeControl) for numerous setting options.
>>>
>>> ~Jason
>>>
>>> --
>>> Jason W. Morgan
>>> Graduate Student
>>> Department of Political Science
>>> *The Ohio State University*
>>> 154 North Oval Mall
>>> Columbus, Ohio 43210
>>>
>>>
>>
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>
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David Winsemius, MD
Heritage Laboratories
West Hartford, CT