[R-sig-ME] What is the lmer/nlme equivalent of the REPEATED subcommand in SPSS's MIXED procedure?
Maarten Jung
Maarten.Jung at mailbox.tu-dresden.de
Wed Mar 21 13:07:31 CET 2018
Dear Ben,
I am a bit puzzled.
Do you mean that
m1 <- gls(value ~ factor1, data, correlation = corSymm(form = ~
1|participant), weights = varIdent(form = ~ 1|factor))
would be equivalent to
m2 <- lmer(value ~ factor1 + (factor1|participant), data)
and one should use gls() because it allows for the same covariance
structures as /REPEATED does?
And, if so, why should m2 cause an identification problem and m1 doesn't?
Regards,
Maarten
On Wed, Mar 21, 2018 at 12:03 PM, Ben Pelzer <b.pelzer at maw.ru.nl> wrote:
> Dear all,
>
> As far as I know, the specification for lmer using
>
> value ~ factor1 + (factor1 | participant)
>
> causes an identification problem, because the residual variance is not
> excluded from the estimations. It would indeed work (e.g. in MlWin this
> can be done) if we could constrain that residual variance to zero. There
> have been some mails in this list about whether or not constraining
> residual variance to zero is possible in lmer, but I believe this is not
> possible. Would be nice if we could do this in lmer!
>
> Best regards, Ben.
>
>
> On 20-3-2018 18:34, Douglas Bates wrote:
> > Kind of looks like SPSS went for bug-for-bug compatibility with SAS on
> > this one. In SAS PROC MIXED, "REPEATED" and "RANDOM" are two ways of
> > specifying the random effects variance structure but they often boil
> > down to the same model.
> >
> > I believe the model can be specified in lme4 as
> >
> > value ~ factor1 + (factor1 | participant)
> >
> > This is what the mis-named* "UNSTRUCTURED" covariance type means
> >
> > * Old-guy, get off my lawn rant about terminology *
> > As a recovering mathematician I find the name "unstructured" being
> > used to denote a positive-definite symmetric matrix to be, well,
> > inaccurate.
> >
> > On Tue, Mar 20, 2018 at 12:19 PM Mollie Brooks
> > <mollieebrooks at gmail.com <mailto:mollieebrooks at gmail.com>> wrote:
> >
> > I don’t know anything about spss, but if you basically want lme4
> > with more correlation structures, you could look at the structures
> > available with glmmTMB.
> > https://cran.r-project.org/web/packages/glmmTMB/
> vignettes/covstruct.html
> >
> > cheers,
> > Mollie
> >
> > > On 20Mar 2018, at 18:11, Ben Pelzer <b.pelzer at maw.ru.nl
> > <mailto:b.pelzer at maw.ru.nl>> wrote:
> > >
> > > Hi Maarten,
> > >
> > > You are right: you need nlme and NOT lme4 to specify particular
> > > correlation structures. Also, in nlme you would need gls to make it
> > > similar to mixed in spss. The repeated command in spss gives the
> > same
> > > results as gls does for any of the covariance structures.
> > >
> > > Regards, Ben.
> > >
> > >
> > > On 20/03/2018 17:30, Maarten Jung wrote:
> > >> Dear Ben, dear Phillip,
> > >>
> > >> comparing [1] with [2] I think the /REPEATED command specifies
> > >> the error (co)variance structure of the model. Would you agree
> > with that?
> > >> If so, AFAIK this is not possible with lmer and thus the answer on
> > >> Stack Overflow [3] would be wrong.
> > >>
> > >> [1]
> > >>
> > https://stats.idre.ucla.edu/r/examples/alda/r-applied-
> longitudinal-data-analysis-ch-7/
> > >> [2]
> > >>
> > https://stats.idre.ucla.edu/spss/examples/alda/chapter7/
> applied-longitudinal-data-analysis-modeling-change-and-
> event-occurrenceby-judith-d-singer-and-john-b-willett-
> chapter-7-examining-the-multilevel-model-s-erro/
> > >> [3]
> > >>
> > https://stackoverflow.com/questions/48518514/what-is-
> the-lmer-nlme-equivalent-of-the-repeated-subcommand-in-spsss-mixed-proc
> > >>
> > >> Regards,
> > >> Maarten
> > >>
> > >> On Tue, Mar 20, 2018 at 2:10 PM, Ben Pelzer <b.pelzer at maw.ru.nl
> > <mailto:b.pelzer at maw.ru.nl>
> > >> <mailto:b.pelzer at maw.ru.nl <mailto:b.pelzer at maw.ru.nl>
> > <mailto:b.pelzer at maw.ru.nl <mailto:b.pelzer at maw.ru.nl>>>> wrote:
> > >>
> > >> Dear Maarten,
> > >>
> > >> Take a look at
> > >>
> > >>
> > https://stats.idre.ucla.edu/r/examples/alda/r-applied-
> longitudinal-data-analysis-ch-7/
> > <https://stats.idre.ucla.edu/r/examples/alda/r-applied-
> longitudinal-data-analysis-ch-7/>
> > >>
> > <https://stats.idre.ucla.edu/r/examples/alda/r-applied-
> longitudinal-data-analysis-ch-7/
> > <https://stats.idre.ucla.edu/r/examples/alda/r-applied-
> longitudinal-data-analysis-ch-7/>>
> > >>
> > >> which shows you a number of covariance structures, among
> > which is
> > >> the unstructured matrix, for repeated measures in R with lme.
> It
> > >> refers to chapter 7 of Singer and Willett where they discuss
> all
> > >> these different structures and how to choose among them.
> > Regards,
> > >>
> > >> Ben.
> > >>
> > >> On 20-3-2018 9:00, Maarten Jung wrote:
> > >>
> > >> Dear list,
> > >> I came across a SPSS syntax like this
> > >>
> > >> MIXED value BY factor1
> > >> /CRITERIA=CIN(95) MXITER(100) MXSTEP(10) SCORING(1)
> > >> SINGULAR(0.000000000001)
> > >> HCONVERGE(0, ABSOLUTE) LCONVERGE(0, ABSOLUTE)
> > >> PCONVERGE(0.000001,
> > >> ABSOLUTE)
> > >> /FIXED=factor1 | SSTYPE(3)
> > >> /METHOD=REML
> > >> /REPEATED=factor1 | SUBJECT(participant) COVTYPE(UN).
> > >>
> > >> and struggle to find an equivalent lmer/nlme (or R in
> > general)
> > >> formulation
> > >> for this kind of models.
> > >> Does anybody know how to convert the REPEATED subcommand
> > into
> > >> R code?
> > >>
> > >> Please note that I asked the question on Stack Overflow
> > about
> > >> two month ago:
> > >>
> > https://stackoverflow.com/questions/48518514/what-is-
> the-lmer-nlme-equivalent-of-the-repeated-subcommand-in-spsss-mixed-proc
> > <https://stackoverflow.com/questions/48518514/what-is-
> the-lmer-nlme-equivalent-of-the-repeated-subcommand-in-spsss-mixed-proc>
> > >>
> > <https://stackoverflow.com/questions/48518514/what-is-
> the-lmer-nlme-equivalent-of-the-repeated-subcommand-in-spsss-mixed-proc
> > <https://stackoverflow.com/questions/48518514/what-is-
> the-lmer-nlme-equivalent-of-the-repeated-subcommand-in-spsss-mixed-proc>>
> > >>
> > >> Best regards,
> > >> Maarten
> > >>
> > >> [[alternative HTML version deleted]]
> > >>
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