I am new to R, ordered logistic regression, and polr.
The "Examples" section at the bottom of the help page for
polr<http://stat.ethz.ch/R-manual/R-patched/library/MASS/html/polr.html>(that
fits a logistic or probit regression model to an ordered factor
response) shows
options(contrasts = c("contr.treatment", "contr.poly"))
house.plr <- polr(Sat ~ Infl + Type + Cont, weights = Freq, data = housing)
pr <- profile(house.plr)
plot(pr)
pairs(pr)
-
What information does pr contain? The help page on
profile<http://stat.ethz.ch/R-manual/R-patched/library/stats/html/profile.html>is
generic, and gives no guidance for polr.
-
What is plot(pr) showing? I see six graphs. Each has an X axis that is
numeric, although the label is an indicator variable (looks like an input
variable that is an indicator for an ordinal value). Then the Y axis is
"tau" which is completely unexplained.
-
What is pairs(pr) showing? It looks like a plot for each pair of input
variables, but again I see no explanation of the X or Y axes.
-
How can one understand if the model gave a good fit?
summary(house.plr)shows Residual Deviance 3479.149 and AIC (Akaike
Information Criterion?) of
3495.149. Is that good? In the case those are only useful as relative
measures (i.e. to compare to another model fit), what is a good absolute
measure? Is the residual deviance approximately chi-squared distributed? Can
one use "% correctly predicted" on the original data or some
cross-validation? What is the easiest way to do that?
-
How does one apply and interpret anova on this model? The docs say "There
are methods for the standard model-fitting functions, including predict,
summary, vcov, anova." However, running anova(house.plr) results in anova
is not implemented for a single "polr" object
-
How does one interpret the t values for each coefficient? Unlike some
model fits, there are no P values here.
I realize this is a lot of questions, but it makes sense to me to ask as one
bundle ("how do I use this thing?") rather than 7 different questions. Any
information appreciated.
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