This data set was analyzed by Weisberg (1980) and Chambers et al. (1983). A catheter is passed into a major vein or artery at the femoral region and moved into the heart. The proper length of the introduced catheter has to be guessed by the physician. The aim of the data set is to describe the relation between the catheter length and the patient's height (X1) and weight (X2).
This data sets is used to demonstrate the effects caused by collinearity. The correlation between height and weight is so high that either variable almost completely determines the other.
A data frame with 12 observations on the following 3 variables.
Patient's height in inches
Patient's weights in pounds
Y: Catheter Length (in centimeters)
There are other
heart datasets in other R packages,
notably survival, hence considering using
package = "robustbase", see examples.
Chambers et al. (1983)
P. J. Rousseeuw and A. M. Leroy (1987) Robust Regression and Outlier Detection; Wiley, p.103, table 13.
data(heart, package="robustbase") heart.x <- data.matrix(heart[, 1:2]) # the X-variables plot(heart.x) covMcd(heart.x) summary( lm.heart <- lm(clength ~ . , data = heart)) summary(lts.heart <- ltsReg(clength ~ . , data = heart))
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