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:
Sex of pupil
SES score of pupil
Minority member 0/1
Number of repeated groups, 0, 1, 2
language score PRE
language score POST
Arithmetic score PRE
Arithmetic score POST
Denomination classification 1-4 - at school level
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
denomina codes are left as missing.
Aggregates are undefined in the presence of missing data
in the underlying values.
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.
https://www.stats.ox.ac.uk/~snijders/mlbook.htm by function
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.
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