[R] r2 question

[Kingsford Jones]

Hi Sarah,

>From your description it sounds as though you would be best off
consulting with a statistician.  Without having a clear understanding
of the research hypotheses, experimental units, how randomization was
performed, the spatial and temporal structure of the experiment, etc,
it's not possible to judge the appropriateness of your
multilevel/hierarchical/mixed model.  Also, R-squared is not defined
from models with random effects (but R-squared-like values can be
calculated for specified levels of variation).  As for how to add
annotation to plots try

example(text) #or
example(plotmath)

hth,
Kingsford Jones




On Sat, Jul 25, 2009 at 6:25 AM, Buckmaster,
Sarah<s.buckmaster.08 at aberdeen.ac.uk> wrote:
> Hi everyone,
>
> I have a question about calculating r-squared in R. I have tried searching the archives and couldn't find what I was looking for - but apologies if there is somewhere I can find this...
>
> I carried out a droughting experiment to test plant competition under limited water. I had:
>  - 7 different levels of watering treatment (1 -7 - from most watered to least watered/)
> - 15 replicates at each level.
>
> Soil moisture readings were taken 4 times throughout the experiment (so I have 105 readings for each of the 4 times) and I now want to check that there was a significant decrease in soil moisture as I decreased the watering frequency, i.e. watering level 7 showed lower soil moisture units than level 1.
>
> I have carried out a repeated measures anova as follows (where block is which time the reading was taken: 1,2,3 or 4):
> model1<-aov(soilmoisture~wateringlevel+Error(block/wateringlevel))
>
> I then plotted (soilmoisture~wateringlevel) and fitted a regression line:
> lm1<-lm(soilmoisture~wateringlevel)
> abline(lm1,lty=1)
>
>
> Here are my questions:
>
> 1) Is the repeated measures anova I have entered correct to tell me if
>  there is a significant difference in my watering levels?
>
> 2) How do I calculate r2 value to show much variation my watering
>  level explains? - and then put this figure on my plot?
>
> Thank you - and again apologies if this is a too-basic question - (I am a real stats and R beginner).
>

No need for apologies --  not too basic at all.
Mixed/Multilevel/Hierarchical models are tricky.  Generally it's not
possible to pass judgment about the appropriateness of a model without
consulting personally with the experimenter -- is it possible for you
to consult with a statistician?  If so, some questions that might
arise include

- For the water effect are you interested in
    - a regression curve describing the effect?
    - effects of each watering level?
    - contrasts between specific levels?
    - interactions between water effect and e.g., location or time?
- What are the experimental units?
- How was randomization performed?
- Is there hierarchical spatial structure (e.g., plants within plots
within blocks)?
- Are there spatial trends in the amount of water applied to units?







> Please let me know if I need to provide any more detail!
>
>
>
> Sarah
>
>        [[alternative HTML version deleted]]
>
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