On Mon, 11 Apr 2011, Elizabeth Pringle wrote:
Hi,
I have a dataset that I am trying to analyze and plot as an ordered logistic
regression (y = ordinal categories 1-3, x = continuous variable with values
3-9).
First is a problem with cdplot:
Produces a beautiful plot, with the "right" trend, but my independent factor
values are transformed. The factor has values from 3-9, but the plot
produces an x-axis with values from 20-140. When I force the xlim to be
3-9, it produces a plot without the trend, which can't be correct.
You transform the presumably numerical regressor "LogAntDensity" to a
factor. Is that intended? If so, cdplot() is not suitable for
visualization as it assumes a numerical x-variable. See ?cdplot.
A more suitable visualization may be obtained using spineplot() which
allows both numerical and categorical x-variables. See ?spineplot.
Second is a problem with polr:
The output of the summary command of the model built with polr includes t
values for lots (if not all) of my independent factor values, but does not
produce a summary of the fit of the model or of the overall fit of the
factor.
You could refit the model without the factor and then compare both models
using anova().
hth,
Z
Also, intercepts are different from those produced with a logistic
fit in JMP...
Code below, any help much appreciated.
Thanks
Beth
LogAntDensityFactor<-as.factor(LogAntDensity)
###order ordinal variable
HammerCatOrd<-ordered(HammerCat)
###set ordered ordinal dependent variable as factor
HammerCatOrdFactor<-as.factor(HammerCatOrd)
###density plot with three levels
cdplot(HammerCatOrdFactor~LogAntDensityFactor,xlab="Log(Ant
Density)",ylab="Latency
of response to disturbance (1-3)")
require(MASS)
logordered<-polr(HammerCatOrdFactor~LogAntDensityFactor,Hess=TRUE)
summary(logordered,digits=3)
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