cutoff. The default
cutoff
is
.2. The fit must come from a function that has
resid(fit, type="dfbetas")
defined.
show.influence, written by Jens Oehlschlaegel-Akiyoshi, applies the
result of
which.influence to a data frame, usually the one used to
fit the model, to report the results.
which.influence(fit, cutoff=.2) show.influence(object, dframe, report=NULL, sig=NULL, id=NULL)
which.influence
signif with
sig digits if
sig is given
dframe if
row.names were
not used
show.influence returns a marked dataframe with the first column being
a count of influence values
Frank Harrell
Department of Biostatistics, Vanderbilt University
f.harrell@vanderbilt.edu
Jens Oehlschlaegel-Akiyoshi
Center for Psychotherapy Research
Christian-Belser-Strasse 79a
D-70597 Stuttgart Germany
oehl@psyres-stuttgart.de
#print observations in data frame that are influential,
#separately for each factor in the model
x1 <- 1:20
x2 <- abs(x1-10)
x3 <- factor(rep(0:2,length.out=20))
y <- c(rep(0:1,8),1,1,1,1)
f <- lrm(y ~ rcs(x1,3) + x2 + x3, x=TRUE,y=TRUE)
w <- which.influence(f, .55)
nam <- names(w)
d <- data.frame(x1,x2,x3,y)
for(i in 1:length(nam)) {
print(paste("Influential observations for effect of ",nam[i]),quote=FALSE)
print(d[w[[i]],])
}
show.influence(w, d) # better way to show results