Here's some code to implement the cheese data table using the proportinal
odds model given in Generalised Linear Models by McCullagh & Nelder (Ch5).
You will have to adapt this to handle your case data - but i'll give you
something to go on.
#### cheese
library(MASS)
options(contrasts = c("contr.treatment", "contr.poly"))
y = c(0,0, 1, 7, 8,8,19, 8,1, 6,9,12,11, 7,6, 1, 0,0, 1,1, 6, 8,23,7, 5,
1,0, 0,0, 0, 1, 3,7,14,16,11)
p =
c(1,2,3,4,5,6,7,8,9,1,2,3,4,5,6,7,8,9,1,2,3,4,5,6,7,8,9,1,2,3,4,5,6,7,8,9)
x1 =
c(1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0)
x2 =
c(0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0)
x3 =
c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0)
ord.rp = ordered(p)
fit0.polr = polr(ord.rp ~ 1, weights=y)
fit1.polr = polr(ord.rp ~ x1 + x2+x3, weights=y)
summary(fit1.polr)
anova(fit0.polr,fit1.polr)
gerard
yongkook Kwon
<yongkookk...@gma
il.com> To
Sent by: [email protected]
r-help-boun...@r- cc
project.org
Subject
[R] how can I ordinal regression??
03/06/2009 08:10
What function and package I use to conduct ordinal regression??
My data is composed 2colums and 180rows.
The first colum indicate level of mass and second colum is intensity.
So, I want to calculate how much intensity are related mass.
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