Chemistry A-level results from one exam board

Description

Chemistry A-level results from one exam board; subset from Yang & Woodhouse, 2001. See also Rasbash et al. (2012) and Browne (2012).

Format

A data frame with 2166 observations on the following 8 variables:

lea

Local Education Authority ID.

estab

Establishment (institution) ID.

pupil

Pupil ID.

a_point

A-level point score (an ordered factor with levels: F, E, D, C, B, A).

gcse_tot

Total GCSE point score.

gcse_no

Number of GCSEs taken.

cons

Constant of ones

gender

Pupil's gender (a factor with levels: male, female).

Details

The alevchem dataset is one of the sample datasets provided with the multilevel-modelling software package MLwiN (Rasbash et al., 2009).

Source

Browne, W. J. (2012) MCMC Estimation in MLwiN Version 2.26. University of Bristol: Centre for Multilevel Modelling.

Rasbash, J., Charlton, C., Browne, W.J., Healy, M. and Cameron, B. (2009) MLwiN Version 2.1. Centre for Multilevel Modelling, University of Bristol.

Rasbash, J., Steele, F., Browne, W.J. and Goldstein, H. (2012) A User's Guide to MLwiN Version 2.26. Centre for Multilevel Modelling, University of Bristol.

Yang, M., Woodhouse, G. (2001) Progress from GCSE to A and AS level: institutional and gender differences, and trends over time. British Educational Research Journal 27: 245-267.

Examples

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## Not run: 

data(alevchem, package = "R2MLwiN")

alevchem$gcseav <- double2singlePrecision(alevchem$gcse_tot/alevchem$gcse_no - 6)

# Note: Establishment codes on their own do not uniquely identify schools.
# Schools are instead uniquely identified by LEA code, establishment ID
# combination. Thus, here we generated a unique school ID.

alevchem$school <- as.numeric(factor(paste0(alevchem$lea, alevchem$estab)))

(mymodel <- runMLwiN(logit(a_point, cons, 6) ~ 1 + gcseav[1:5] + I(gcseav^2)[1:5] +
  gender[1:5] + (1[1:5] + gcseav[1:5] | school), 
  D = "Ordered Multinomial", estoptions = list(EstM = 1), data = alevchem))


## End(Not run)

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