[R-sig-ME] (no subject)

[Ben Bolker]

Yes.  I think you can specify a fixed residual variance in blme::blmer, but
not to exactly zero.

On Thu, Aug 2, 2018 at 12:24 AM Peter Paprzycki <peter.paprzycki using gmail.com>
wrote:

> Sorry, you estimated it to be very close to zero, I see.
> Peter
>
> On Wed, Aug 1, 2018 at 11:08 PM, Peter Paprzycki <
> peter.paprzycki using gmail.com> wrote:
>
>> Perfect. Thank you. It is good to know that we can specify the
>> random-effects variance
>> equal to zero. Thanks.
>> Peter
>>
>>
>> <http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail> Virus-free.
>> www.avg.com
>> <http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail>
>> <#m_3076315220315282584_m_981606773260833816_DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2>
>>
>> On Wed, Aug 1, 2018 at 10:57 PM, Ben Bolker <bbolker using gmail.com> wrote:
>>
>>>
>>>   (please keep r-sig-mixed-models in the Cc:)
>>>
>>>   I'm pretty sure that lmer and lm models are commensurate, in case that
>>> helps.  Here's an example rigged to make the random-effects variance
>>> equal to zero, so we can check that the log-likelihoods etc. are
>>> identical.
>>>
>>> set.seed(101)
>>> dd <- data.frame(y=rnorm(20),x=rnorm(20),f=factor(rep(1:2,10)))
>>> library(lme4)
>>> m1 <- lmer(y~x+(1|f),data=dd,REML=FALSE) ## estimated sigma^2_f=0
>>> m2 <- lm(y~x,data=dd)
>>> all.equal(c(logLik(m1)),c(logLik(m2))) ## TRUE
>>> all.equal(fixef(m1),coef(m2))
>>> anova(m1,m2)
>>>
>>>
>>> On 2018-08-01 11:41 PM, Peter Paprzycki wrote:
>>> > Thank you. Oh, was just trying to compare my random-effects model to
>>> the
>>> > one where my grouping variable (schools) is treated as fixed.
>>> >
>>> > Peter
>>> >
>>> > <
>>> http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail
>>> >
>>> >       Virus-free. www.avg.com
>>> > <
>>> http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail
>>> >
>>> >
>>> >
>>> > <#DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2>
>>> >
>>> > On Wed, Aug 1, 2018 at 10:32 PM, Ben Bolker <bbolker using gmail.com
>>> > <mailto:bbolker using gmail.com>> wrote:
>>> >
>>> >
>>> >       I'm not 100% sure I understand the question, but I think the
>>> answer is
>>> >     "no": lmer cannot fit a model that doesn't contain any random
>>> effects.
>>> >     Perhaps you can give more context as to why it won't work for you
>>> to
>>> >     revert to lm() or plm() in these cases?
>>> >
>>> >     On 2018-08-01 11:30 PM, Peter Paprzycki wrote:
>>> >     > This is very basic, is there a way to specify in lmer function
>>> >     that I would
>>> >     > like to run my grouping variable as a fixed factor only, without
>>> >     reverting
>>> >     > to lm or plm functions. If one does not specify a random
>>> variable,
>>> >     one gets
>>> >     > the error message with lmer function; something that is
>>> equivalent
>>> >     to the
>>> >     > statement, "index = "grouping variable", model = "within"" with
>>> >     the plm
>>> >     > function.
>>> >     >
>>> >     >
>>> >     <
>>> http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail
>>> >     <
>>> http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail
>>> >>
>>> >     > Virus-free.
>>> >     > www.avg.com <http://www.avg.com>
>>> >     >
>>> >     <
>>> http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail
>>> >     <
>>> http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail
>>> >>
>>> >     > <#DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2>
>>> >     >
>>> >     >       [[alternative HTML version deleted]]
>>> >     >
>>> >     > _______________________________________________
>>> >     > R-sig-mixed-models using r-project.org
>>> >     <mailto:R-sig-mixed-models using r-project.org> mailing list
>>> >     > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>> >     <https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models>
>>> >     >
>>> >
>>> >
>>> >
>>> >
>>> > --
>>> >
>>> > Peter Paprzycki, Ph.D.
>>> > Visiting Assistant Professor
>>> > Research Support Center Manager
>>> >
>>> > Educational Research and Administration
>>> > College of Education and Psychology
>>> > The University of Southern Mississippi
>>> > USM Box 5093; 118 College Drive
>>> > Hattiesburg, Mississippi 39406-0001
>>> > tel. (601)-266-4708
>>> > email: Peter.Paprzycki using usm.edu <mailto:Peter.Paprzycki using usm.edu>
>>> >
>>> >
>>> > Sidere mens eadum mutato
>>> >
>>>
>>
>>
>>
>> --
>>
>> Peter Paprzycki, Ph.D.
>> Visiting Assistant Professor
>> Research Support Center Manager
>>
>> Educational Research and Administration
>> College of Education and Psychology
>> The University of Southern Mississippi
>> USM Box 5093; 118 College Drive
>> Hattiesburg, Mississippi 39406-0001
>> tel. (601)-266-4708
>> email: Peter.Paprzycki using usm.edu
>>
>>
>> Sidere mens eadum mutato
>>
>
>
>
> --
>
> Peter Paprzycki, Ph.D.
> Visiting Assistant Professor
> Research Support Center Manager
>
> Educational Research and Administration
> College of Education and Psychology
> The University of Southern Mississippi
> USM Box 5093; 118 College Drive
> Hattiesburg, Mississippi 39406-0001
> tel. (601)-266-4708
> email: Peter.Paprzycki using usm.edu
>
>
> Sidere mens eadum mutato
>

	[[alternative HTML version deleted]]