[R-sig-ME] What is the lmer/nlme equivalent of the REPEATED subcommand in SPSS's MIXED procedure?
Douglas Bates
bates at stat.wisc.edu
Tue Mar 20 18:34:24 CET 2018
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>
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> 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>>> 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]]
> >>
> >> _______________________________________________
> >> R-sig-mixed-models at r-project.org <mailto:
> R-sig-mixed-models at r-project.org>
> >> <mailto:R-sig-mixed-models at r-project.org <mailto:
> R-sig-mixed-models at 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>
> >> <https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models <
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models>>
> >>
> >>
> >> _______________________________________________
> >> R-sig-mixed-models at r-project.org <mailto:
> R-sig-mixed-models at r-project.org>
> >> <mailto:R-sig-mixed-models at r-project.org <mailto:
> R-sig-mixed-models at 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>
> >> <https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models <
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models>>
> >>
> >>
> >
> >
> > [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > R-sig-mixed-models at r-project.org <mailto:
> R-sig-mixed-models at 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>
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
[[alternative HTML version deleted]]
More information about the R-sig-mixed-models
mailing list