id_me: Calculate ideal point marginal effects

In saudiwin/idealstan: Robust Measurement with 'Stan'

Calculate ideal point marginal effects

Description

This function allows you to calculate ideal point marginal effects for a given person-level hierarchical covariate.

Usage

id_me(object, ...)

Arguments

object	A fitted idealstan model
...	Other values passed on to methods.

Details

This function will calculate item-level ideal point marginal effects for a given covariate that was passed to the id_make function using the person_cov option. The function will iterate over all items in the model and use numerical differentiation to calculate responses in the scale of the outcome for each item. Note: if the covariate is binary (i.e., only has two values), then the function will calculate the difference between these two values instead of using numerical differentation.

Value

Returns a tibble that has one row per posterior draw per item-specific marginal effect in the scale of the outcome.

saudiwin/idealstan documentation built on April 11, 2025, 4:37 p.m.