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...@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]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.