Hi again, I am getting an error message from the code below that the expression is ill-formed. I realize that this is due probably to some mismatch between a real and a vector, but I admit I am stumped by it. The error message and code are below. If someone could point me to where I can learn more about how to work with these variable/parameter types for typical regression models, it would be most helpful. Thanks

David

## Expression is ill formed.

error in ‘modele3a3784cab5_bea2581e0976fcdbf559189af41e6a59’ at line 36, column 45

```
34:
35: alpha[g] ~ normal(mu_alpha[g], sigma_alpha);
36: mu_alpha[g] = gamma00+gamma01*ACBG03A[g];
^
37: beta1[g] ~ normal(mu_beta1, sigma_beta1);
```

Error in stanc(file = file, model_code = model_code, model_name = model_name, :

failed to parse Stan model ‘bea2581e0976fcdbf559189af41e6a59’ due to the above error.

The code is here:

modelString = "

data {

int<lower=0> n; // number of students

int<lower=0> G; // number of schools

int<lower=1,upper=G> schid[n]; // school indices

```
vector[n] ASRREA01; // reading outcome variable
vector[n] ASBG04;
vector[G] ACBG03A;
```

}

parameters {

real gamma00[G];

real gamma01[G];

real alpha[G];

real beta1[G];

real mu_beta1[G];

real sigma_read[n];

real sigma_alpha[G];

real sigma_beta1[G];

}

model {

vector[n] mu;

vector[G] mu_alpha;

for (i in 1:n) {

ASRREA01[i] ~ normal(mu[i], sigma_read);

mu[i] = alpha[schid[i]] + beta1[schid[i]]*ASBG04[i];

}

for (g in 1: G) {

```
alpha[g] ~ normal(mu_alpha[g], sigma_alpha);
mu_alpha[g] = gamma00+gamma01*ACBG03A[g];
beta1[g] ~ normal(mu_beta1, sigma_beta1);
```

}

// Priors

gamma00 ~ normal(300,100);

gamma01 ~ normal(11, 1);

mu_beta1 ~ normal(20, 2);

sigma_read ~ cauchy(1,5);

sigma_alpha ~ cauchy(1,5);

sigma_beta1 ~ cauchy(1,5);

}

"