augPred plot in nlme library

plot(augPred(fm2c))

Thanks Deepayan and Andrew.

msMaxIter solved the convergence problem and plot(augPred) works with
my data when I employ I() in the function call.

One other strange thing I noticed is that when I take logs of
dependent variable in the function call, the plot of augPred 
doesn't graph any prediction line at all.  

contr=nlmeControl(msMaxIter = 500)
fm2c <- lme(log(distance) ~ age + I(age^2), data = Orthodont,
control=contr)
plot(augPred(fm2c)) 

However, this is fixed by hard coding the dependent variable:

log.dist = log(distance)
fm2c <- lme(log.dist ~ age + I(age^2), data = Orthodont,
control=contr) plot(augPred(fm2c))



-----Original Message-----
From: Deepayan Sarkar [mailto:deepayan.sarkar at gmail.com] 
Sent: Saturday, September 09, 2006 11:46 AM
To: Afshartous, David
Cc: Andrew Robinson; r-help at stat.math.ethz.ch
Subject: Re: [R] augPred plot in nlme library

On 9/9/06, Afshartous, David <afshart at exchange.sba.miami.edu> wrote: >
Hi Andrew, > > Thanks for your email.  I assume you mean age^2 instead
of age.2 for > fm2a, and for fm2b, I get the following error: > > >
fm2b <- lme(distance ~ age + I(age^2), data = Orthodont) > Error in
lme.formula(distance ~ age + I(age^2), data = Orthodont) : >        
iteration limit reached without convergence (9) > > do you get his
error as well?

For me, adding 'control = list(msMaxIter = 500)' worked. I'm writing
from memory, so the name may not be exactly right, see ?nlmeControl.

Finally, the Pixel example on p.42 of Pinheiro & Bates gets the
quadratic plot w/o using I() as you do below; is this due to a
difference between S and R?

Yes.

thanks!
dave

ps - sorry for not making the data available; if anyone is
interested please let me know and I'll send it directly.




-----Original Message-----
From: Andrew Robinson [mailto:A.Robinson at ms.unimelb.edu.au]
Sent: Friday, September 08, 2006 5:46 PM
To: Afshartous, David
Cc: Deepayan Sarkar; r-help at stat.math.ethz.ch
Subject: Re: [R] augPred plot in nlme library

Hi David,

this is the sort of thing that Deepayan meant.  Make a dataset
available to us, or use one that will be installed by default on R.

eg

require(nlme)
fm1 <- lme(distance ~ age, data = Orthodont)
plot(augPred(fm1))

#  All linear

fm2a <- lme(distance ~ age + age.2, data = Orthodont)
plot(augPred(fm2a))

# Still linear

fm2b <- lme(distance ~ age + I(age^2), data = Orthodont)
plot(augPred(fm2b))

# Quadratic!

I hope that this helps you resolve the problem.

Andrew



On Fri, Sep 08, 2006 at 05:18:13PM -0400, Afshartous, David wrote:

Deepayan,

Thanks for your suggestion.  Here are more details:

I have a grouped data object for repeated measures data just like
the Pixel grouped data object on p.42 of Pinheiro and Bates
(2000).

comp.adj.UKV.3 <- groupedData(adj.UKV ~ Time |

Patient_no/Lisinopril,

      data = comp.adj.UKV.frm, order.groups = F
      #labels = list(x = "Hour", y = "adj.UKV")
)

i.e., the response is continuous, Time is not treated as a factor,
and

there exists two factors, one nested within the other (Lisinopril
nested

witin patient, similar to Side within Dog on p.42).

I also fit a model very similar to their model:

fm1comp = lme(adj.UKV ~ Time + Time.sq, data = comp.adj.UKV.3,
random = list(Patient_no = ~ 1 , Lisinopril = ~ 1) )


However, the command below does not produce the fitted curves from
this model, but rather it seems to be the fitted curves from a
linear model.

plot(augPred(fm3comp))

Possibly augPred behaves differently in R than in S, but reading
the

R

help and trying various other approaches has not solved this.

Thanks!
Dave




-----Original Message-----
From: Deepayan Sarkar [mailto:deepayan.sarkar at gmail.com]
Sent: Friday, September 08, 2006 4:37 PM
To: Afshartous, David
Cc: r-help at stat.math.ethz.ch
Subject: Re: [R] augPred plot in nlme library

On 9/8/06, Afshartous, David <afshart at exchange.sba.miami.edu>
wrote:

All,

I've solved part of the problem below by making sure that the
formula in the grouped data object is the same as the formula
specified within

lme (this isn't the case in the cited example from Pinheiro &

Bates).

However, augPred seems to plot only a linear model instead of
the polynomial model.  Does anyone know how to make sure that
augPred plots the same model as that specified in the model (as
below)?

You are unlikely to get any helpful answers unless you give us
more information, as every r-help message asks you to do:

R-help at stat.math.ethz.ch mailing list 

-Deepayan