Thanks to Harold Doran for pointing out the modification to the control
argument.  I should have suspected that I was doing something wrong when I
couldn't get even simple lmer calls to work.  At any rate, here is the
revised table.

           Setup   T30   D620    T30   D620    D620    D620
Model \ Function  samm   samm   lmer   lmer   lmer2     lme
----------------  ----   ----   ----   ----   -----   -----
yrs|id + yrs|sch     f      f   30.0     34    65
yrs|id +   1|sch  10.5    7.8   13.7     14    23
  1|id + yrs|sch   9.4    9.5   11.5   11.8     7.3
  1|id +   1|sch   6.5    5.7    5.6    4.1     5.4      60
         yrs|sch   4.8    4.0      f    0.4     0.5
           1|sch   3.4    2.2    0.4    0.3     0.3       4
yrs|id             5.7    5.7    8.2    7.4    15       150
  1|id             4.1    3.4    2.4    1.6     4.2      14

I know that I can use "yrs|sch" instead of "1+yrs|sch", but I find that R's
implicit intercepts make reading the code more obtuse than when including
explicit intercepts.  Maybe I'm an obtuse user.  YMMV.

Kevin Wright

(Sorry for HTML...used to ensure proper formatting of the table)



On 2/1/07, Doran, Harold <HDoran@air.org> wrote:
>
> Try adding this portion of code to your lmer model
>
> control=list(gradient = FALSE, niterEM = 0)
>
> This will change what you have below from
>
> lmer(math~ gr + sx + eth + cltype + (1+yrs|id) + (1+yrs|sch), data=star)
>
> To
>
> lmer(math~ gr + sx + eth + cltype + (1+yrs|id) + (1+yrs|sch), data=star,
> control=list(gradient = FALSE, niterEM = 0))
>
> BTW, you don't need (1+yrs) you can reduce this to just (yrs|id).
>
> This should make a huge difference.
>
> Harold
>
>
> > -----Original Message-----
> > From: r-sig-mixed-models-bounces@r-project.org
> > [mailto:r-sig-mixed-models-bounces@r-project.org] On Behalf
> > Of Kevin Wright
> > Sent: Thursday, February 01, 2007 10:25 AM
> > To: r-sig-mixed-models@r-project.org
> > Subject: [R-sig-ME] Timings with SAMM, lme4, nlme
> >
> > About a year and a half ago I did some comparison of model
> > fitting with SAMM, lme4, and nlme.  Since Doug Bates put out
> > a request for some recent timings, I am repeating/extending
> > my comparisons.  In the interim, I have switched computers,
> > so the timings of the samm function facilitate comparing the
> > speed across the two computers.
> >
> > First, the results (view with fixed-width font)
> >
> >            Setup   T30   D620    T30   D620     D620    D620
> > Model \ Function  samm   samm   lmer   lmer    lmer2     lme
> > ----------------  ----   ----   ----   ----    -----   -----
> > yrs|id + yrs|sch     f      f   30.0   kill     65
> > yrs|id +   1|sch  10.5    7.8   13.7   kill     23
> >   1|id + yrs|sch   9.4    9.5   11.5   kill      7.3
> >   1|id +   1|sch   6.5    5.7    5.6   kill      5.4      60
> >          yrs|sch   4.8    4.0      f   kill      0.5
> >            1|sch   3.4    2.2    0.4    0.7      0.3       4
> > yrs|id             5.7    5.7    8.2   kill     15       150
> >   1|id             4.1    3.4    2.4   kill      4.2      14
> >
> > In the table above, "Setup" refers to the following two computer
> > configurations:
> >
> > T30:  IBM Thinkpad T30, 1 GB ram, 1.8 Ghz processor, Windows 2000
> >       SAMM version 1.1, lme4 & nlme current on 5.24.2005
> >
> > D620: Dell Latitude D620, 2 GB ram, 1.8 Ghz duo core processor, WinXP
> >       SAMM version 1.1 lme4 & nlme current as of 1.30.2007
> >
> > I timed most model fits only once.  I did a quick inspection
> > of the results from the different modelling functions to
> > persuade myself that I was fitting the same model (i.e. that
> > estimates were similar).
> >
> > Here are the full models I used:
> >
> > lmer(math~ gr + sx + eth + cltype + (1+yrs|id) + (1+yrs|sch),
> > data=star)
> >
> > samm(math ~ gr + sx + eth + cltype, random=~ us(link(~1+yrs)):id +
> >      us(link(~1+yrs)):sch, data=star, na.method.X="omit")
> >
> > Starting with these full models, I tried reduced models with
> > simpler random effects structures.  These are the different
> > rows in the table above.
> >
> > Observations:
> > (1) The performance of the common version of SAMM on the two
> > computers suggests the Dell is slightly faster than the IBM.
> >
> > (2) On 24 May 2005, lmer and samm has roughly similar
> > timings.  On 31 Jan 2007, lmer is nearly unusable for this
> > data (I killed the job after 5-10 minutes of waiting).
> >
> > (3) The current version of lmer2 is the only function that
> > appears to fit all models.
> >
> > (4) The current version of lme is slower than sammm/lmer2 for
> >     those models I tried to fit.
> >
> > FYI.  SAMM is officially available at
> > http://www.vsni.co.uk/products/samm/(but seems not to be
> > there now, perhaps in preparation for release of a new
> > version). Unofficially it is available here: ftp://ftp.dpi.nsw.gov.au/
> >
> > I hope this information is useful.  Thanks for the progress
> > evident in the
> > lme4 package.
> >
> > Kevin Wright
> >
> >       [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > R-sig-mixed-models@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >
>

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