[R-sig-ME] lmer vs lmer2

[Henric Nilsson (Private)]

Quoting Martin Maechler <maechler at stat.math.ethz.ch>:

>>>>>> "DB" == Douglas Bates <bates at stat.wisc.edu>
>>>>>>     on Thu, 6 Sep 2007 11:17:17 -0500 writes:
>
>     DB> On 9/6/07, Bush, Andrew J <abush at utmem.edu> wrote:
>     >> Dear Douglas,
>
>     >> In frustration, I invoked lmer2 this morning and I'm pleased   
> to be able
>     >> to tell you that lmer2 copes well and quickly with the model having a
>     >> random intercept and two random covariate slopes.  I have not  
>  been able
>     >> to get lmer to converge for the model on the same data.
>
>     DB> Thanks for the information.
>
>     DB> I expect to remove the confusion between lmer and lmer2 in the near
>     DB> future.  The development version of the lme4 package has an lmer
>     DB> function that is close to the current lmer2 in design.  It should
>     DB> exhibit the same convergence behavior and be slightly faster  
>  on models
>     DB> fit to large data sets than is the current lmer2.
>
>     DB> This version has been in development for longer than I had expected.
>     DB> I still have a few "infelicities" to resolve in the Laplace   
> method for
>     DB> generalized linear mixed models before I make test versions   
> available.
>
>     DB> I would be interested in the data set if you would be willing to
>     DB> provide it.  I could perhaps incorporate it in the lme4 package so
>     DB> others would have access to it.
>
> Yes, indeed.
> The example might be particularly interesting as test case, not
> only because some software implementations "converge" with
> singular covariance matrix, but also because it
> differs from other examples in having "many" fixed effects and
> just one level random effects.

The data set in question, and, I belive, most others from Fitzmaurice,  
Laird and Ware's (2004) book on longitudinal data analysis, is  
available along with accompanying SAS programs at

http://biosun1.harvard.edu/~fitzmaur/ala/

In particular, the data used above is here

http://biosun1.harvard.edu/~fitzmaur/ala/fev1.txt

and the SAS code is here

http://biosun1.harvard.edu/~fitzmaur/ala/prog8_8.html


HTH,
Henric



>
> Martin
>
>     >> -----Original Message-----
>     >> From: dmbates at gmail.com [mailto:dmbates at gmail.com] On Behalf   
> Of Douglas
>     >> Bates
>     >> Sent: Wednesday, September 05, 2007 9:22 PM
>     >> To: ajbush at bellsouth.net
>     >> Cc: r-sig-mixed-models at r-project.org
>     >> Subject: Re: [R-sig-ME] Specifying random effects for multiple
>     >> covariates via lmer
>     >>
>     >> On 9/5/07, Andy Bush <ajbush at bellsouth.net> wrote:
>     >> > While working through the text "Applied Longitudinal Analysis" by
>     >> > Fitzmaurice, Laird and Ware, I encountered a fairly simple   
> case study
>     >> (pp
>     >> > 210-7) in which a longitudinal model specifies three random effects:
>     >> (1)
>     >> > random intercepts for id, (2) random slopes for covariate1   
> (Age | id),
>     >> and
>     >> > (3) random slopes for covariate2 (log(ht) | id).  I've had no
>     >> difficulty
>     >> > formulating lmer models with correlated random intercepts and slopes
>     >> for
>     >> > either of the covariates individually but have not succeeded when I
>     >> try to
>     >> > compose a model with correlated random intercepts and slopes for two
>     >> > covariates.
>     >>
>     >> > Following is code that works well with the individual covariates
>     >> separately:
>     >>
>     >> > m1=lmer(LFEV1~Age + loght + InitAge + logbht + (1 + Age |
>     >> id),data=fev,
>     >> >        na.action=na.omit, method="REML")
>     >>
>     >> > m2=lmer(LFEV1~Age + loght + InitAge + logbht+(1 + loght |
>     >> id),data=fev,
>     >> >        na.action=na.omit, method="REML")
>     >>
>     >> Maybe I am missing the point but wouldn't the model you are
>     >> considering be written as
>     >>
>     >> lmer(LFEV1 ~ Age + loght + InitAge + logbht + (loght + Age|id), data =
>     >> fev, na.action = na.omit, method = "REML")
>     >>
>     >> That provides correlated random effects for the intercept, the
>     >> coefficient for loght and the coefficient for Age at each level of the
>     >> id factor.
>     >>
>
>     DB> _______________________________________________
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