# R Dataset / Package MASS / nlschools

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## Visual Summaries

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<iframe src="https://embed.picostat.com/r-dataset-package-mass-nlschools.html" frameBorder="0" width="100%" height="307px" />
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54.72 KB
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Dataset Help

On this Picostat.com statistics page, you will find information about the nlschools data set which pertains to Eighth-Grade Pupils in the Netherlands. The nlschools data set is found in the MASS R package. You can load the nlschools data set in R by issuing the following command at the console data("nlschools"). This will load the data into a variable called nlschools. If R says the nlschools data set is not found, you can try installing the package by issuing this command install.packages("MASS") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the nlschools R data set. The size of this file is about 56,037 bytes.

Documentation

## Eighth-Grade Pupils in the Netherlands

### Description

Snijders and Bosker (1999) use as a running example a study of 2287 eighth-grade pupils (aged about 11) in 132 classes in 131 schools in the Netherlands. Only the variables used in our examples are supplied.

### Usage

nlschools


### Format

This data frame contains 2287 rows and the following columns:

lang

language test score.

IQ

verbal IQ.

class

class ID.

GS

class size: number of eighth-grade pupils recorded in the class (there may be others: see COMB, and some may have been omitted with missing values).

SES

social-economic status of pupil's family.

COMB

were the pupils taught in a multi-grade class (0/1)? Classes which contained pupils from grades 7 and 8 are coded 1, but only eighth-graders were tested.

### Source

Snijders, T. A. B. and Bosker, R. J. (1999) Multilevel Analysis. An Introduction to Basic and Advanced Multilevel Modelling. London: Sage.

### References

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

### Examples

nl1 <- within(nlschools, {
IQave <- tapply(IQ, class, mean)[as.character(class)]
IQ <- IQ - IQave
})
cen <- c("IQ", "IQave", "SES")
nl1[cen] <- scale(nl1[cen], center = TRUE, scale = FALSE)nl.lme <- nlme::lme(lang ~ IQ*COMB + IQave + SES,
random = ~ IQ | class, data = nl1)
summary(nl.lme)
--

Dataset imported from https://www.r-project.org.