lm() with spearman corr option ?
I think you would just need to replace the lm() function call with cor(x,y,method="spearman". It would probably be more informative to actually plot by the magnitude of the correlation coefficient (all |r| >= 0.20 or something similar) rather than just by those with P <=0.05. Brian Brian S. Cade, PhD U. S. Geological Survey Fort Collins Science Center 2150 Centre Ave., Bldg. C Fort Collins, CO 80526-8818 email: cadeb at usgs.gov <brian_cade at usgs.gov> tel: 970 226-9326
On Thu, Apr 28, 2016 at 9:35 PM, Hoji, Akihiko <akh22 at pitt.edu> wrote:
Hi,
A following function was kindly provided by GGally?s maintainer, Barret
Schloerke.
function(data, mapping, ...) {
p <- ggplot(data = data, mapping = mapping) +
geom_point(color = I("blue")) +
geom_smooth(method = "lm", color = I("black"), ...) +
theme_blank() +
theme(panel.border=element_rect(fill=NA, linetype = "solid",
color="black"))
lmModel <- eval(substitute(lm(y ~ x, data = data), mapping))
fs <- summary(lmModel)$fstatistic
pValue <- pf(fs[1], fs[2], fs[3], lower.tail = FALSE)
if (pValue < 0.05) {
p <- p + theme(
panel.border = element_rect(
color = "red",
size = 3,
linetype = "solid",
fill = "transparent"
)
)
}
p
}
Basically, this function draws red squares over pairwise corr plots with
p<0.05. Now, since I need to use the spearman rank corr, I tried to modify
the lm function by adding ?method=spearman? but this did not work at al.
Could anybody suggest the way to add the spearman rank corr function in
this particular function ?
Thanks.
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