candisc plotting
Dear Pete, You haven't told us what your data is, and we can only surmise -- not very helpful for you and annoying for those who try to help.
Pete Shepard wrote:
Hello,
I have a file with two dependent variables (three and five) and one
independent variable. I do i.mod <- lm(cbind(three, five) ~ species,
data=i.txt) and get the following output:
Coefficients:
three five
(Intercept) 9.949 9.586
species -1.166 -1.156
From this, it seems that species is numeric variable, not a factor. If so, canonical discriminant analysis in not appropriate, so all following bets are off. That's likely why you end up with only one canonical dimension.
I do a" i.can<-candisc(i.mod,data=i):
Is data=i the same as data=i.txt?
and get the following output:
Canonical Discriminant Analysis for species:
CanRsq Eigenvalue Difference Percent Cumulative
1 0.096506 0.10681 100 100
Test of H0: The canonical correlations in the
current row and all that follow are zero
LR test stat approx F num Df den Df Pr(> F)
1 0.903 63.875 1 598 6.859e-15 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
this is different than the output I get with SAS:
What was your SAS code? Was the data the same?
Eigenvalue Difference Proportion Cumulative Ratio F Value
Num DF Den DF Pr > F
1 0.1068 1.0000 1.0000 0.90349416
31.88 2 597 <.0001
I am also wondering how to plot the can1*can1 like it is done in SAS.
proc plot;
plot can1*can1=species;
format species spechar.;
title2 'Plot of Constits_vs_cassettes';
run;
If you want to compare plots for canonical analysis in SAS and R, see my macros, canplot and hecan at http://www.math.yorku.ca/SCS/sasmac/ But in general, if all you have is 1 canonical dimension, a dotplot or boxplot of the canonical scores would be more useful than a scatterplot plot of can1 * can1. The plot method for candisc objects in the candisc package has some code to handle the 1 can-D case. hope this helps -Michael
Thanks [[alternative HTML version deleted]]
______________________________________________ R-help at 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.
Michael Friendly Email: friendly AT yorku DOT ca Professor, Psychology Dept. York University Voice: 416 736-5115 x66249 Fax: 416 736-5814 4700 Keele Street http://www.math.yorku.ca/SCS/friendly.html Toronto, ONT M3J 1P3 CANADA