Hello everybody,

I analyzed a 46 dichotomous items matrix using the Bayesian 1PL (brms R package). Here is the synthax I used:

```
formula_va_1pl <- bf(Xb16 ~ 1 + (1 | It16) + (1 | P16))
prior_va_1pl <- prior("normal(0, 3)", class = "sd", group = "It16") + prior("normal(0, 3)", class = "sd", group = "P16")
fit_va_1pl <- brm(formula = formula_va_1pl,
data = X16,
family = brmsfamily("bernoulli","logit"),
prior = prior_va_1pl)
```

I wish to extract the MCMC chains of every items under investigation. I find that posterior_samples function need to be used here. For example:

```
samples <- posterior_samples(fit_va_1pl,)
```

Nevertheless, I don’t understand clearly what is the specific MCMC chain values for the first chain regarding difficulty of item 4 for example.

` Thanking you VERY MUCH in advance…`