unreplicated repeated measures

It's a old post found by searching.
Dear R users,

Sorry if this question is not applicable to this site. I am having problems
analysing unreplicated repeated measures. I calculated food web properties
for three treatments over time (10 months). It is unreplicated in that I
only have one observation per month per treatment. My problem is that I am
interested in how a food web property varies between Treatments and over
time.

I have a similar data set, and hope to do similar statistical analysis.
Originally I had tried using lmer:
m4<-lmer(lncon~Treatment*month+(1|month),data=dataset)
but this provides the following error for which I have not found an
explanation to on the R site.
Error in mer_finalize(ans) : Calculated PWRSS for a LMM is negative
gls() in nlme package was recommended to deal with my situation. 
However, I don't know how to describe the fixed effects:

gls(lncon~Treatment*month, data = dataset)

or

gls(lncon~Treatment+month, data = dataset)

It seems that the above two formula can run correctly, however, I don't 
know which one should be preferred, and whether the variable month 
should be treated as a factor or a continuous variable. I have read the 
book of Pinheiro & Bates, and found the time variable in dataset, e.g., 
Orthodont, is a numeric vector. What's the difference?

Is it possible to intercept the data by lme() or lmer(), for there is no 
group variable?

<snip>

Any suggestions or comments will be really appreciated. Thanks in advance.

Regards,
Jinsong
An artificial data:

  Trt     Time          Yield
    1     1983     -1.3249564
    1     1986      0.7196249
    1     1993      0.1483918
    1     1998      0.1739599
    1     2003     -0.5962691
    1     2010     -0.1382644
    2     1983     -0.5212350
    2     1986     -0.5751201
    2     1993     -0.7656928
    2     1998      1.0399397
    2     2003      1.5328539
    2     2010     -0.5204021
    3     1983      0.9821412
    3     1986     -0.4376944
    3     1993     -1.2453136
    3     1998     -0.3852303
    3     2003     -1.9200383
    3     2010      0.2154259

Thanks again for your attention.

Regards,
Jinsong
It's a old post found by searching.

On 2009-6-24 1:29, Christine Griffiths wrote:
Dear R users,

Sorry if this question is not applicable to this site. I am having
problems
analysing unreplicated repeated measures. I calculated food web
properties
for three treatments over time (10 months). It is unreplicated in that I
only have one observation per month per treatment. My problem is that
I am
interested in how a food web property varies between Treatments and over
time.

I have a similar data set, and hope to do similar statistical analysis.

Originally I had tried using lmer:
m4<-lmer(lncon~Treatment*month+(1|month),data=dataset)
but this provides the following error for which I have not found an
explanation to on the R site.
Error in mer_finalize(ans) : Calculated PWRSS for a LMM is negative
gls() in nlme package was recommended to deal with my situation.
However, I don't know how to describe the fixed effects:

gls(lncon~Treatment*month, data = dataset)

or

gls(lncon~Treatment+month, data = dataset)

It seems that the above two formula can run correctly, however, I don't
know which one should be preferred, and whether the variable month
should be treated as a factor or a continuous variable. I have read the
book of Pinheiro & Bates, and found the time variable in dataset, e.g.,
Orthodont, is a numeric vector. What's the difference?

Is it possible to intercept the data by lme() or lmer(), for there is no
group variable?

<snip>

Any suggestions or comments will be really appreciated. Thanks in advance.

Regards,
Jinsong

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