I am trying to run the ordered logit model pasted below and am running into the following issue.

All transitions after warmup exceed a maximum treedepth of 12. This is the only warning I am getting after I fit the model, yet the Rhats are incredibly high and n_eff is 2, so I don’t believe the model converged.

When launching shinystan, I also see that the traceplots do not look like the chains mixed and the stepsize parameter is zero for all chains.

What might be wrong with the model such that it is not converging even though there were no divergent transitions? I thought that exceeding max treedepth was only a computational efficiency issue, not an issue of convergence.

Thanks so much for any tips you may have.

```
data{
int<lower=0> n; // number of data points
int<lower=0> j; // number of item parameters
int<lower=2> k; // number of cutpoints
int y1[n];
int y2[n];
int y3[n];
int y4[n];
}
parameters{
vector[j] alpha; // item difficulty parameters
real<lower=0> beta[j]; // item discrimination parameters
vector[n] theta; // latent variables
real<lower=0> sigma[j]; // standard deviations
ordered[k-1] c1; // cutpoints
ordered[k-1] c2; // cutpoints
ordered[k-1] c3; // cutpoints
ordered[k-1] c4; // cutpoints
}
model{
theta ~ normal(0, 1); // fixing latent variable scale
alpha ~ normal(0, 10); // prior on item difficulty
beta ~ gamma(4, 3); // prior on item discrimination
y1 ~ ordered_logistic(alpha[1] + beta[1] * theta, c1);
y2 ~ ordered_logistic(alpha[2] + beta[2] * theta, c2);
y3 ~ ordered_logistic(alpha[3] + beta[3] * theta, c3);
y4 ~ ordered_logistic(alpha[4] + beta[4] * theta, c4);
}
```