从 rms 中获取残差诊断图 package ols() function

Question

How do you obtain residual diagnostic plots from an ols() object? normally if using glm() or lm() , I'd just do plot(lm()) , but plot(ols()) gives an error.

My code is:

fit <- ols(y ~ rcs(x1,4)*x2, data=data, x=TRUE, y=TRUE)
plot(fit)

The error message I receive is

Error in match.arg(type): 'arg' should be one of “ordinary”, “score”, “dfbeta”, “dfbetas”, “dffit”, “dffits”, “hat”, “hscore”

Answer 1

Laboriously (but flexibly), you need to compute residuals and estimates (using resid() and fitted() ) and bind them into your data frame, then use plotting package like ggplot2 or lattice to create the plots yourself. Harrell gives examples at bottom of p. 153 of the 2nd edition of his book that describes the use of this package in detail.

As a quick and dirty alternative, you can fit a version using conventional functions (eg lm() ) and plot() will return the usual diagnostic plots. Things like rcs() will work with many of the base fitting functions.

Answer 2

The ols object does inherit from the lm object,

class(rcsLogFit)
## [1] "ols" "rms" "lm" 

but I was unable to gets stats:::lm() to work without the error noted here.

A quick workaround is to make a copy that forgets its rms -specific classes:

rcsLogCopy <- rcsLogFit
class(rcsLogCopy) <- "lm"

and then

plot(rcsLogCopy)

works fine. I suppose you could do this directly on the original instead.