I'm following along with this official IRT w/ STAN tutorial. The details of the model are copied below:
data {
int<lower=1> J; // number of students
int<lower=1> K; // number of questions
int<lower=1> N; // number of observations
int<lower=1,upper=J> jj[N]; // student for observation n
int<lower=1,upper=K> kk[N]; // question for observation n
int<lower=0,upper=1> y[N]; // correctness for observation n
}
parameters {
real delta; // mean student ability
real alpha[J]; // ability of student j - mean ability
real beta[K]; // difficulty of question k
}
model {
alpha ~ std_normal(); // informative true prior
beta ~ std_normal(); // informative true prior
delta ~ normal(0.75, 1); // informative true prior
for (n in 1:N)
y[n] ~ bernoulli_logit(alpha[jj[n]] - beta[kk[n]] + delta);
}
I'm not certain which variables do and do not need to be declared in R code.
toy_data <- list(
J= 5,
K = 4,
N =20,
y= c(1,1,1,1,1,1,1,0,1,1,0,0,1,0,0,0,0,0,0,0)
)
fit <- stan(file = '1PL_stan.stan', data = toy_data)
However, the following error is triggered.
Error in mod$fit_ptr() :
Exception: variable does not exist; processing stage=data initialization; variable name=jj; base type=int (in 'model920c4330dff_1PL_stan' at line 5)
In addition: Warning messages:
1: In readLines(file, warn = TRUE) :
incomplete final line found on 'C:\Users\jacob.moore\Downloads\1PL_stan.stan'
2: In system(paste(CXX, ARGS), ignore.stdout = TRUE, ignore.stderr = TRUE) :
'-E' not found
failed to create the sampler; sampling not done
In my past work, I've used python almost exclusively. So learning R has been quite the learning curve; additionally, I'm very new to STAN, hence the toy example.
The core idea is that there are 20 child/question pairings. 5 children and 4 different questions. I'm uncertain why my code is triggering the error, and what I should do to correct it. Can you clarify what needs adjustment for this code to run without triggering an error?
Every parameter listed in the data block (J, K, N, jj, kk, and y) needs to be included in the variable toy_data. You've left out jj and kk.
You have 5 students (J=5) answering 4 questions each (K=4). jj is the student ID, and kk is the question ID, so assuming your responses are ordered by student and then by question, you would have something like
jj = c(1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5)
kk = c(1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4)