ordered logistic regression - cdplot and polr
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) [[alternative HTML version deleted]]
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