Description Usage Format Details Source Examples

School Data, from Charnes et al. (1981). The aim is to explain scores on 3
different tests, `reading`

, `mathematics`

and `selfesteem`

from 70 school sites by means of 5 explanatory variables.

1 |

A data frame with 70 observations on the following 8 variables.

`education`

education level of mother as measured in terms of percentage of high school graduates among female parents

`occupation`

highest occupation of a family member according to a pre-arranged rating scale

`visit`

parental visits index representing the number of visits to the school site

`counseling`

parent counseling index calculated from data on time spent with child on school-related topics such as reading together, etc.

`teacher`

number of teachers at a given site

`reading`

total reading score as measured by the Metropolitan Achievement Test

`mathematics`

total mathematics score as measured by the Metropolitan Achievement Test

`selfesteem`

Coopersmith Self-Esteem Inventory, intended as a measure of self-esteem

This dataset was shamelessly borrowed from the `FRB`

package.

The relationships among these variables are unusual, a fact only revealed by plotting.

A. Charnes, W.W. Cooper and E. Rhodes (1981). Evaluating Program and Managerial Efficiency: An Application of Data
Envelopment Analysis to Program Follow Through. *Management Science*, **27**, 668-697.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ```
data(schooldata)
# initial screening
plot(schooldata)
# better plot
library(corrgram)
corrgram(schooldata, lower.panel=panel.ellipse, upper.panel=panel.pts)
#fit the MMreg model
school.mod <- lm(cbind(reading, mathematics, selfesteem) ~
education + occupation + visit + counseling + teacher, data=schooldata)
# shorthand
school.mod <- lm(cbind(reading, mathematics, selfesteem) ~ ., data=schooldata)
Anova(school.mod)
heplot(school.mod)
heplot3d(school.mod)
# robust model, using robmlm()
school.rmod <- robmlm(cbind(reading, mathematics, selfesteem) ~ ., data=schooldata)
# note that counseling is now significant
Anova(school.rmod)
# compare classical HEplot with robust
heplot(school.mod, cex=1.4, lty=1, fill=TRUE, fill.alpha=0.1)
heplot(school.rmod, add=TRUE, error.ellipse=TRUE, lwd=c(2,2), lty=c(2,2),
term.labels=FALSE, err.label="", fill=TRUE)
``` |

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