I came across a dataset on UK schools that has scores, student / school gender information. After some digging on the Net, I found a sample Bugs model for this data, so I decided to give it a try. The data file was mentioned here http://dss.princeton.edu/training/Multilevel101.pdf and is at http://dss.princeton.edu/training/schools.dta.
I converted this data Python readable format and saved it as testing.dat. Sample Bugs model was at http://www.cmm.bristol.ac.uk/learning-training/multilevel-m-software/reviewwinbugs.pdf
Other useful info: http://www.cmm.bristol.ac.uk/learning-training/multilevel-m-software/reviewaml.pdf
The example code is written in Python / JAGS. The model can certainly be improved. Keyword dflat() does not seem to be supported anymore, so dnorm(0.0,1.0E-6) was used instead when necessary.
Data and recent code
import rpy2.robjects as R
import rpy2.rinterface as rinterface
from rpy2.robjects.packages import importr
import rpy2.robjects.numpy2ri
from rpy2.robjects.vectors import FloatVector, StrVector
import numpy as np
r2jags = importr('R2jags')
schools = np.loadtxt("testing.dat", skiprows=1)
n=len(schools)
J = np.unique(np.max(schools[:,0]))[0]
y = schools[:,2]
school = schools[:,0]
standlrt = schools[:,3] # reading score
gender = schools[:,4] # student gender
school_gender = schools[:,5] # school gender, 1 mixed, 2 boys, 3 girls,
boysch = np.zeros(n)
boysch[school_gender == '2'] = 1
girlsch = np.zeros(n)
girlsch[school_gender == '3'] = 1
R.r.assign('n',n)
R.r.assign('J',J)
R.r.assign('y',y)
R.r.assign('school',school)
R.r.assign('standlrt',standlrt)
R.r.assign('gender',gender)
R.r.assign('boysch',boysch)
R.r.assign('girlsch',girlsch)
jags_data = StrVector(("n", "J", "y", "school", "standlrt", "gender", "boysch", "girlsch"))
jags_params = StrVector(("a", "beta","tau.y", "tau.a"))
jags_inits = R.r('''function (){
list (a=rnorm(J),mu=rnorm(1),sigma.y=runif(1), sigma.a=runif(1))
}''')
jags_schools = r2jags.jags(data = jags_data, inits = jags_inits,
parameters_to_save = jags_params,
n_iter = 10000,
n_chains = 3, n_thin = 100,
model_file = "testing.bug")
print jags_schools
I converted this data Python readable format and saved it as testing.dat. Sample Bugs model was at http://www.cmm.bristol.ac.uk/learning-training/multilevel-m-software/reviewwinbugs.pdf
Other useful info: http://www.cmm.bristol.ac.uk/learning-training/multilevel-m-software/reviewaml.pdf
The example code is written in Python / JAGS. The model can certainly be improved. Keyword dflat() does not seem to be supported anymore, so dnorm(0.0,1.0E-6) was used instead when necessary.
Data and recent code
import rpy2.robjects as R
import rpy2.rinterface as rinterface
from rpy2.robjects.packages import importr
import rpy2.robjects.numpy2ri
from rpy2.robjects.vectors import FloatVector, StrVector
import numpy as np
r2jags = importr('R2jags')
schools = np.loadtxt("testing.dat", skiprows=1)
n=len(schools)
J = np.unique(np.max(schools[:,0]))[0]
y = schools[:,2]
school = schools[:,0]
standlrt = schools[:,3] # reading score
gender = schools[:,4] # student gender
school_gender = schools[:,5] # school gender, 1 mixed, 2 boys, 3 girls,
boysch = np.zeros(n)
boysch[school_gender == '2'] = 1
girlsch = np.zeros(n)
girlsch[school_gender == '3'] = 1
R.r.assign('n',n)
R.r.assign('J',J)
R.r.assign('y',y)
R.r.assign('school',school)
R.r.assign('standlrt',standlrt)
R.r.assign('gender',gender)
R.r.assign('boysch',boysch)
R.r.assign('girlsch',girlsch)
jags_data = StrVector(("n", "J", "y", "school", "standlrt", "gender", "boysch", "girlsch"))
jags_params = StrVector(("a", "beta","tau.y", "tau.a"))
jags_inits = R.r('''function (){
list (a=rnorm(J),mu=rnorm(1),sigma.y=runif(1), sigma.a=runif(1))
}''')
jags_schools = r2jags.jags(data = jags_data, inits = jags_inits,
parameters_to_save = jags_params,
n_iter = 10000,
n_chains = 3, n_thin = 100,
model_file = "testing.bug")
print jags_schools
