R2MLwiN (version 0.8-2)

jspmix1: Dataset of pupils' test scores, a subset of the Junior School Project.

Description

An educational dataset of pupils' test scores, a subset of the Junior School Project (Mortimore et al., 1988).

Format

A data frame with 1119 observations on the following 8 variables:

school

School identifying code.

id

Pupil identifying code.

sex

Sex of pupil; a factor with levels female and male.

fluent

Fluency in English indicator, where 0 = beginner, 1 = intermediate, 2 = fully fluent; measured in Year 1.

ravens

Test score, out of 40; measured in Year 1.

english

Pupils' English test score, out of 100; measured in Year 3.

behaviour

Pupils' behaviour score, where lowerquarter = pupil rated in bottom 25%, and upper otherwise; measured in Year 3.

cons

A column of ones. If included as an explanatory variable in a regression model (e.g. in MLwiN), its coefficient is the intercept.

Source

Browne, W. J. (2012) MCMC Estimation in MLwiN Version 2.26. University of Bristol: Centre for Multilevel Modelling. Mortimore, P., Sammons, P., Stoll, L., Lewis, D., Ecob, R. (1988) School Matters. Wells: Open Books. Rasbash, J., Charlton, C., Browne, W.J., Healy, M. and Cameron, B. (2009) MLwiN Version 2.1. Centre for Multilevel Modelling, University of Bristol.

Details

A subset of the Junior School Project (Mortimore et al., 1988), the jspmix1 dataset is one of the sample datasets provided with the multilevel-modelling software package MLwiN (Rasbash et al., 2009), and is used in Browne (2012) as an example of modelling mixed responses. It consists of test scores for 1119 pupils across 47 schools. Note that the behaviour variable originally had three categories, and the middle 50% and top 25% have been combined to produce a binary variable.)

Examples

## Not run: 
# 
# data(jspmix1, package = "R2MLwiN")
# 
# jspmix1$denomb <- jspmix1$cons
# 
# (mymodel <- runMLwiN(c(english, probit(behaviour, denomb)) ~ 
#   1 + sex + ravens + fluent[1] + (1 | school) + (1[1] | id), 
#   D = c("Mixed", "Normal", "Binomial"), 
#   estoptions = list(EstM = 1, mcmcMeth = list(fixM = 1, residM = 1, Lev1VarM = 1)), 
#   data = jspmix1))
# 
# ## End(Not run)