[R] how to interpret the results of a simint call
Hi all,
I've done some anovas, found some significance and proceeded to do the
post hoc tests to determine the source of the significance. I used the
multcmp package as suggested by Andy Liaw (thank you).
I am, however, unsure how to interpret the results of the call to
simint. Could someone help me with this?
I've attached the code and the results it produced. There are 3 groups
(ctrl,long,short) and I'm trying to see if the data in the Mean_12
column (in the example below) differs based on group membership.
for (meanCol in meanColumns) {
roi.err.aov-aov(eval(parse(text=meanCol)) ~ Group, data=roi.errs);
HSD.err-simint(eval(parse(text=meanCol)) ~ Group, data=roi.errs,
type=Tukey);
cat(\n);
cat(### Summary of AOV for , meanCol, cluster: , i, \n);
print(summary(roi.err.aov))
print(summary(HSD.err))
i-i+1;
}
### Summary of AOV for Mean_12 cluster: 12
Df Sum Sq Mean Sq F value Pr(F)
Group2 6368494 3184247 8.8536 0.001627 **
Residuals 21 7552730 359654
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Simultaneous 95% confidence intervals: Tukey contrasts
Call:
simint.formula(formula = eval(parse(text = meanCol)) ~ Group,
data = roi.stops, type = Tukey)
Tukey contrasts for factor Group
Contrast matrix:
Groupctrl Grouplong Groupshort
Grouplong-Groupctrl 0-1 1 0
Groupshort-Groupctrl 0-1 0 1
Groupshort-Grouplong 0 0-1 1
Absolute Error Tolerance: 0.001
95 % quantile: 2.519
Coefficients:
Estimate2.5 % 97.5 % t value Std.Err. p raw p Bonf
Grouplong-Groupctrl -134.246 -930.286 661.794 -0.425 316.076 0.675 1.000
Groupshort-Groupctrl 978.056 182.016 1774.097 3.094 316.076 0.005 0.016
Groupshort-Grouplong 1112.303 400.303 1824.303 3.934 282.707 0.001 0.002
p adj
Grouplong-Groupctrl 0.906
Groupshort-Groupctrl 0.015
Groupshort-Grouplong 0.002
Thanks in advance,
Regards,
Colm.
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[R] recommendation for post-hoc tests after anova
Greetings all, I've done some ANOVAs and have found significant effects across my groups, so now I have to do some post-hoc tests to ascertain which of the groups is driving the significant effect. Usually one would do something like a Newman-Keuls or Scheffe test to get at this but based on googling and browsing through the r-help archives R doesn't support these and they seem to be badly received by the R community generally (for reasons related to alpha not being properly controlled, if I understand correctly). I found the TukeyHSD function but on reading the help page, I'm unsure whether it's safe for me to use it since the number of subjects in my groups is not balanced (ctrl=6, short=9, long=9). Would you reckon that this is mildly unbalanced in the spirit of the help page or that is my caution warranted? In the absence of NK or Scheefe tests could someone recommend an appropriate test for me to conduct in this instance? From what I've read in Explaining Psychological Statistics, the REGWQ test seems to be the way to go. Can R perform this test? Thanks for your time, Regards, -- Dr Colm G. Connolly School of Psychology and Institute of Neuroscience The Lloyd Building University of Dublin Trinity College, Dublin 2, Éire __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] reference paper about SOM
On eof the best sources of info on the SOM is Kohonen's book. Try and
get this if you can.
@Book{kohonen95:_self,
author = {Teuvo Kohonen},
title ={Self-organizing maps},
publisher ={Springer},
year = 1995,
address = {Berlin}
}
On 01/04/06, Linda Lei [EMAIL PROTECTED] wrote:
Hi All,
I'm looking for some reference paper about SOM (self organizing map)
algorithm. I tried the paper which is mentioned in
the help page of function som (package:som):
http://www.cis.hut.fi/research/papers/som_tr96.ps.Z
But I can't open it for some reason. Could you please help me with it ?
Thanks a lot!
[[alternative HTML version deleted]]
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[R] variables as arguments in formulae in aov?
Hi all,
I wonder if you could help me with (what is surely) a simple R question?
I've written a simple R script (attached) to perform multiple ANOVAs
on the columns in a table loaded in from a a file (also attached). I
loop through the list of columns for which I want to perform the
ANOVAs, storing the column name in a variable. When I try to perform
the ANOVA using the variable name as a reference to the column name R
complains as follows:
Error in the model.frame(formula, rownames, variables, varnames,
extras, extranames, :
invalid variable type
The line causing the problem is the first line inside the for loop.
The question is what have I done wrong? Is there a better way of doing
the ANOVAs?
Thanks in advance,
Bye,
Colm.
roi.errs=read.table(../Group.results/allGroupsROI.errs, header=T, sep=\t);
roi.stops=read.table(../Group.results/allGroupsROI.stops, header=T, sep=\t);
# extract the names of the columns containing the means
roi.names=names(roi.errs);
meanColumns=roi.names[4:length(roi.names)];
## open the output file, split=T also spits it to the screen
sink(../Group.results/ROI.errs.txt,split=T)
cat(\n);
cat(*** Summary for ROI.errs\n);
for (meanCol in meanColumns) {
roi.err.aov-aov(meanCol ~ Group, data=roi.errs);
cat(\n);
cat(*** Summary of AOV for , meanCol, \n);
summary(roi.err.aov);
}
## close the output file
sink();
## open the output file, split=T also spits it to the screen
sink(../Group.results/ROI.stops.txt,split=T)
cat(\n);
cat(*** Summary for ROI.stops\n);
for (meanCol in meanColumns) {
roi.stops.aov-aov(meanCol ~ Group, data=roi.stops);
cat(\n);
cat(*** Summary of AOV for , meanCol, \n);
summary(roi.stops.aov);
}
## close the output file
sink();
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