 Hello list,
I am trying to analyze a model with lme, but I could use some clarification
on the proper syntax for dealing with the nested nature of my experiment.
I have two fixed factors (soil strength = 4 levels; competition = 4 levels)
applied separately to 6 replicate pots per treatment combination (n = 96
pots).  Within the pots I took several measurements on two plants per pot.  The
ultimate goal of the experiment is to understand how the two factors affect
plant performance. Although some measurements from the two plants
(subsamples) can be averaged (e.g., height, number of leaves), others that
may be important covariates in the model cannot be averaged (e.g., time
since being galled).  So, I need to retain information on individual plants
even though they are obviously subsamples within pot.  Any advice would be
appreciated.

Here is a snippet of my data for context:

pot           plant.ID   soil.strength            competition
avg.PAR   initial.height           weeks.galled           final.height

1              1.1           A                              D
467                          34                            4
112

1              1.2           A                              D
467                          23                            0
156

2              2.1           C                              B
345                          27                            9
104

2              2.2           C                              B
345                          28                            7
123

3              3.1           D                              A
436                          31                            0
147

3              3.2           D                              A
436                          33                            0
154

…and here is a (most likely incorrect) example of how I’d like to model
these data:
lme(final.height ~ avg.PAR + weeks.galled + competition*soil.strength,
random = ~1|pot)

Best,

Chris

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