dgirt.Rddgirt and dgmrp make calls to stan with
the Stan code and data for their respective models.
dgirt(shaped_data, ..., separate_t = FALSE, delta_tbar_prior_mean = 0.65, delta_tbar_prior_sd = 0.25, innov_sd_delta_scale = 2.5, innov_sd_theta_scale = 2.5, version = "2017_01_04", hierarchical_model = TRUE, model = NULL) dgmrp(shaped_data, ..., separate_t = FALSE, delta_tbar_prior_mean = 0.65, delta_tbar_prior_sd = 0.25, innov_sd_delta_scale = 2.5, innov_sd_theta_scale = 2.5, version = "2017_01_04_singleissue", model = NULL)
| shaped_data | Output from |
|---|---|
| ... | Further arguments, passed to |
| separate_t | Whether smoothing of estimates over time should be
disabled. Default |
| delta_tbar_prior_mean | Prior mean for |
| delta_tbar_prior_sd | Prior standard deviation for |
| innov_sd_delta_scale | Prior scale for |
| innov_sd_theta_scale | Prior scale for |
| version | The name of the dgo model to estimate, or the path to a
|
| hierarchical_model | Whether a hierarchical model should be used to
smooth the group IRT estimates. If set to FALSE, the model will return raw
group-IRT model estimates for each group. Default |
| model | A Stan model object of class |
A dgo_fit-class object that extends
stanfit-class.
The user will typically pass further arguments to stan
via the ... argument, at a minimum iter and cores.
By default dgirt and dgmrp override the
stan default for its pars argument to specify
typical parameters of interest. They also set iter_r to 1L.
Important: the dgirt model assumes consistent coding of the polarity
of item responses for identification.