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Anova
3 messages · daniel jupiter, Gavin Simpson, Douglas Bates
On Sat, 2008-03-15 at 12:48 -0500, daniel jupiter wrote:
Hi all, I apologize for what might be a silly question. I am interested in doing a one way anova. This is not too hard in and of itself, either with anova, aov or oneway.test . However, I need to 1) get pvalues,
if obj is the result of anova, aov, oneway.test, then
str(obj) ## for anova
str(summary(obj)) ## for aov
str(obj) ## for oneway.test
to find the names of the elements of obj that contain the p-values of
the various tests/models. In the first two you are looking for the
component "Pr(>F)" and the latter is obvious ("p.value")
For summary(aov) objects, the result is a list so this gets the p-value
you need:
obj[[1]]$`Pr(>F)` or obj[[1]][,5]]
for anova then this:
obj$`Pr(>F)` or obj[,5]
note the quoting of the component name using backticks.
For oneway.test
obj$p.value
2) do a posthoc analysis with Tukey HSD,
?TukeyHSD for the results of aov
3) and have (sometimes) an unbalanced design.
See ?lme in package nlme
I just can't seem to put all the pieces together. Any suggestions?
I'm not sure what the problem is here - you don't say. All of what I say above is documented in the relevant help pages for the various functions and using str() is a basic tenet of using R and looking at returned objects. Ok, you might have needed help with getting the p-values for some of those tests/models, but 2) and 3) are answered on ?aov For what you describe, stick with aov for balanced designs if you want to do TukeyHSD as there is a method for aov objects (otherwise) you'll need to refit the model. For unbalanced designs, check out lme and for that you may need to get/borrow the book by Pinhiero and Bates, reference details of which are given in item [7] on: http://www.r-project.org/doc/bib/R-books.html
Thanks in advance, Dan.
HTH G
%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% Dr. Gavin Simpson [t] +44 (0)20 7679 0522 ECRC, UCL Geography, [f] +44 (0)20 7679 0565 Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/ UK. WC1E 6BT. [w] http://www.freshwaters.org.uk %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
1 day later
On Sun, Mar 16, 2008 at 6:39 AM, Gavin Simpson <gavin.simpson at ucl.ac.uk> wrote:
On Sat, 2008-03-15 at 12:48 -0500, daniel jupiter wrote:
> Hi all, > > I apologize for what might be a silly question. > > I am interested in doing a one way anova. > This is not too hard in and of itself, either with anova, aov or oneway.test > . > > However, I need to > 1) get pvalues,
if obj is the result of anova, aov, oneway.test, then
str(obj) ## for anova
str(summary(obj)) ## for aov
str(obj) ## for oneway.test
to find the names of the elements of obj that contain the p-values of
the various tests/models. In the first two you are looking for the
component "Pr(>F)" and the latter is obvious ("p.value")
For summary(aov) objects, the result is a list so this gets the p-value
you need:
obj[[1]]$`Pr(>F)` or obj[[1]][,5]]
for anova then this:
obj$`Pr(>F)` or obj[,5]
note the quoting of the component name using backticks.
For oneway.test
obj$p.value
> 2) do a posthoc analysis with Tukey HSD,
?TukeyHSD for the results of aov
> 3) and have (sometimes) an unbalanced design.
See ?lme in package nlme
> > I just can't seem to put all the pieces together. > > Any suggestions?
I'm not sure what the problem is here - you don't say. All of what I say above is documented in the relevant help pages for the various functions and using str() is a basic tenet of using R and looking at returned objects. Ok, you might have needed help with getting the p-values for some of those tests/models, but 2) and 3) are answered on ?aov For what you describe, stick with aov for balanced designs if you want to do TukeyHSD as there is a method for aov objects (otherwise) you'll need to refit the model. For unbalanced designs, check out lme and for that you may need to get/borrow the book by Pinhiero and Bates, reference details of which are given in item [7] on: http://www.r-project.org/doc/bib/R-books.html
Thanks for the plug, Gavin, but lme and my book with Jose are for linear *mixed-effects* models. I think the question here is about unbalanced fixed-effects models and those can be fit quite simply by lm, aov and friends. Users, quite reasonably, expect that model fitting in R is done using the formulas that they saw in an introductory textbook. In fact, that is almost never the case. Functions like lm and aov use computational methods that do not depend on balance in the data.
> > Thanks in advance, > > Dan. >
HTH G -- %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% Dr. Gavin Simpson [t] +44 (0)20 7679 0522 ECRC, UCL Geography, [f] +44 (0)20 7679 0565 Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/ UK. WC1E 6BT. [w] http://www.freshwaters.org.uk %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
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