[R-sig-ME] repeated measurement using mixed model

[Jinsong Zhao]

On 2011-11-18 21:32, Christoph Scherber wrote:
> Dear Jinsong Zhao,
>
> In this case, you may wish to use a generalized least squares model (gls), also to be found in the nlme library. You can start with an initial model
> containing only fixed effects, and then update it with an appropriate correlation structure.
>
> Try this first:
>
> library(nlme)
> ?gls
> ?corStruct
>
> All the best
> Christoph

Dear Christoph,

Thank you very much for the kindly reply.

Dose gls() fit the linear model without random effects? Is corStruct 
used with correlation argument to explore the structure of residual 
variance?

Another question, someone suggests that replications of response 
variable, e.g., determined concentration on 3 samples obtained from same 
treatment, should be include in the design. Then, the random effects 
could be estimated (I don't know how), and it will improve the power of 
statistical analysis. I don't think so, however, I can't find a way to 
explain that.

Regards,
Jinsong

>
> on 18.11.2011 07:29, Jinsong Zhao wrote:
>
>> Hi there,
>>
>> We have got a valuable data set from a long-term experiment. The
>> experimental design is following:
>>
>> Trt     Time     Y
>>     1     1983
>>     1     1986
>>     1     1993
>>     1     1998
>>     1     2003
>>     1     2010
>>     2     1983
>>     2     1986
>>     2     1993
>>     2     1998
>>     2     2003
>>     2     2010
>>     3     1983
>>     3     1986
>>     3     1993
>>     3     1998
>>     3     2003
>>     3     2010
>>
>> Because the data was collected in a way of repeated measurement. we
>> think it should be analyzed using linear mixed model. However, there is
>> no group variable, and as you have noted, there is no replication for
>> each treatment (Trt). So, we don't know how to deal with this data set.
>>
>> Any suggestions or comments will be really appreciated. Thanks in advance.
>>
>> Regards,
>> Jinsong
>>
>> _______________________________________________
>> R-sig-mixed-models at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>
>> .
>>
>
>