Dear All:
I tried to replicate a case study described by Prof. Harrell in Chapter 7 of
his Regression Modeling Strategies book, but failed on using plot to
reproduce partial effects diagram in figure 7.9, Following is the code:
rm(list=ls())
library(Hmisc)
getHdata(counties)
counties$older <- counties$age6574 + counties$age75
label(counties$older) <- '% age >= 65, 1990'
counties$pdensity <- log10(counties$pop.density+1)
label(counties$pdensity) <- 'log 10 of 1992 pop per 1990 miles^2'
dd <- datadist(counties)
options(datadist='dd')
f <- ols(democrat ~ rcs(pdensity,4) + rcs(pop.change,3) + rcs(older,3) +
crime + rcs(college,5)
+ rcs(income,4) + rcs(college,5) %ia% rcs(income,4) + rcs(farm,3) +
rcs(white,5) +
rcs(turnout,3), data=counties)
f
plot(f, ylim = c(20,70))
and the error message reads as:
Error in match.arg(type) :
'arg' should be one of “ordinary”, “score”, “dfbeta”, “dfbetas”,
“dffit”, “dffits”, “hat”, “hscore”
Does anyone have a clue?
Regards,
Sebastian
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