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 [[alternative HTML version deleted]]