[R-sig-ME] Difference lme4 and nlme

[Andrzej Galecki]

Hello to everyone,

Actually, the same type of mistake occurred in an earlier email.


"If you do indeed want to have PARTY nested within J then your call to
lmer should use the formula

REVENUES ~ INCUMBENCY + (1|PARTY) + (1|J:PARTY)"


Preferred notation was used incorrectly. It should be:

REVENUES ~ INCUMBENCY + (1|J) + (1|J:PARTY)


Thank you

Andrzej Galecki
University of Michigan








On 2/23/2011 10:39 AM, Douglas Bates wrote:
> On Wed, Feb 23, 2011 at 8:39 AM, ONKELINX, Thierry
> <Thierry.ONKELINX at inbo.be>  wrote:
>> "(1|PARTY) + (1|J:PARTY)" and "(1|J/PARTY)" are equal
> Actually (1|PARTY) + (1|J:PARTY) is equal to (1|PARTY/J).  It is easy
> to confuse these which is why I prefer not to use the (1|F/G)
> notation.
>
>> "(1|PARTY) + (1|J:PARTY)" and "(J|PARTY)" are not equal
>>
>> ----------------------------------------------------------------------------
>> ir. Thierry Onkelinx
>> Instituut voor natuur- en bosonderzoek
>> team Biometrie&  Kwaliteitszorg
>> Gaverstraat 4
>> 9500 Geraardsbergen
>> Belgium
>>
>> Research Institute for Nature and Forest
>> team Biometrics&  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-sig-mixed-models-bounces at r-project.org
>>> [mailto:r-sig-mixed-models-bounces at r-project.org] Namens Iker
>>> Vaquero Alba
>>> Verzonden: woensdag 23 februari 2011 15:30
>>> Aan: Daniel; Douglas Bates
>>> CC: R-sig-mixed-models at r-project.org
>>> Onderwerp: Re: [R-sig-ME] Difference lme4 and nlme
>>>
>>>
>>>
>>>     Just a technical question: Would "(1|PARTY) + (1|J:PARTY)"
>>> be equal to "(1|J/PARTY)" and this to "(J|PARTY)"?
>>>
>>>     I've tried the last two ones and as long as I saw, I got
>>> the same results, but I might have overlooked something.
>>>
>>>     Thank you. Regards.
>>>
>>>     Iker
>>>
>>> --- El mié, 23/2/11, Douglas Bates<bates at stat.wisc.edu>  escribió:
>>>
>>> De: Douglas Bates<bates at stat.wisc.edu>
>>> Asunto: Re: [R-sig-ME] Difference lme4 and nlme
>>> Para: "Daniel"<dmsilv at gmail.com>
>>> CC: R-sig-mixed-models at r-project.org
>>> Fecha: miércoles, 23 de febrero, 2011 15:08
>>>
>>> Notice that the first model has 27 levels for J and the
>>> second model has 465 levels for PARTY %in% J.  That's the difference.
>>>
>>> If you do indeed want to have PARTY nested within J then your
>>> call to lmer should use the formula
>>>
>>> REVENUES ~ INCUMBENCY + (1|PARTY) + (1|J:PARTY)
>>>
>>>
>>> On Wed, Feb 23, 2011 at 6:27 AM, Daniel<dmsilv at gmail.com>  wrote:
>>>> Hello list,
>>>>
>>>> I'm just try to find out how can I produce the results
>>> using both packages.
>>>> Perhaps I'm using different equation. Trailer model are
>>> consistent to
>>>> Stata output using (tmixed REVENUES INCUMBENCY || J: || PARTY:)
>>>>
>>>> lme2<-
>>> lmer(REVENUES~INCUMBENCY+(1|J)+(1|PARTY),data=data,na.action =
>>>> "na.omit", REML=TRUE)
>>>>
>>>> Linear mixed model fit by REML
>>>> Formula: REVENUES ~ INCUMBENCY + (1 | J) + (1 | PARTY)
>>>>   Data: data
>>>>   AIC   BIC logLik deviance REMLdev
>>>> 78123 78153 -39057    78154   78113
>>>> Random effects:
>>>> Groups   Name        Variance   Std.Dev.
>>>> J        (Intercept) 9.6263e+08  31026 PARTY    (Intercept)
>>> 1.7502e+09
>>>> 41836 Residual             3.0534e+10 174741 Number of obs: 2894,
>>>> groups: J, 27; PARTY, 27
>>>>
>>>> Fixed effects:
>>>>            Estimate Std. Error t value
>>>> (Intercept)    34244      11657   2.938 INCUMBENCY    211495
>>>> 9536  22.178
>>>>
>>>> Correlation of Fixed Effects:
>>>>           (Intr)
>>>> INCUMBENCY -0.097
>>>>
>>>> lme3<- lme(REVENUES~INCUMBENCY, random=~1
>>>> |J/PARTY,data=data,na.action = "na.omit", REML=TRUE)
>>>>
>>>> Linear mixed-effects model fit by REML
>>>>   Data: data
>>>>   Log-restricted-likelihood: -39078.07
>>>>   Fixed: REVENUES ~ INCUMBENCY
>>>> (Intercept)  INCUMBENCY
>>>>    52469.19   220521.74
>>>>
>>>> Random effects:
>>>>   Formula: ~1 | J
>>>>         (Intercept)
>>>> StdDev:    25424.31
>>>>
>>>>   Formula: ~1 | PARTY %in% J
>>>>         (Intercept) Residual
>>>> StdDev:     45574.5 173465.7
>>>>
>>>> Number of Observations: 2894
>>>> Number of Groups:
>>>>            J PARTY %in% J
>>>>           27          465
>>>>
>>>> --
>>>> Daniel Marcelino
>>>> Skype: dmsilv
>>>> http://sites.google.com/
>>>>
>>>>         [[alternative HTML version deleted]]
>>>>
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