brandsma | R Documentation |

Dataset with raw data from Snijders and Bosker (2012) containing data from 4106 pupils attending 216 schools. This dataset includes all pupils and schools with missing data.

`brandsma`

is a data frame with 4106 rows and 14 columns:

`sch`

School number

`pup`

Pupil ID

`iqv`

IQ verbal

`iqp`

IQ performal

`sex`

Sex of pupil

`ses`

SES score of pupil

`min`

Minority member 0/1

`rpg`

Number of repeated groups, 0, 1, 2

`lpr`

language score PRE

`lpo`

language score POST

`apr`

Arithmetic score PRE

`apo`

Arithmetic score POST

`den`

Denomination classification 1-4 - at school level

`ssi`

School SES indicator - at school level

This dataset is constructed from the raw data. There are a few differences with the data set used in Chapter 4 and 5 of Snijders and Bosker:

All schools are included, including the five school with missing values on

`langpost`

.Missing

`denomina`

codes are left as missing.Aggregates are undefined in the presence of missing data in the underlying values. Variables

`ses`

,`iqv`

and`iqp`

are in their original scale, and not globally centered. No aggregate variables at the school level are included.There is a wider selection of original variables. Note however that the source data contain an even wider set of variables.

Constructed from `MLbook_2nded_total_4106-99.sav`

from
https://www.stats.ox.ac.uk/~snijders/mlbook.htm by function
`data-raw/R/brandsma.R`

Brandsma, HP and Knuver, JWM (1989), Effects of school and classroom characteristics on pupil progress in language and arithmetic. International Journal of Educational Research, 13(7), 777 - 788.

Snijders, TAB and Bosker RJ (2012). Multilevel Analysis, 2nd Ed. Sage, Los Angeles, 2012.

mice documentation built on June 7, 2023, 5:38 p.m.

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