Detect IRT/process change points using an SIC-inspired multichannel score

This implementation is a transparent package reference inspired by the 2026 SIC-CPA literature. It combines Bernoulli response likelihood with normal log-RT and standardized gaze likelihoods. It is not a line-for-line reproduction of the article's estimator.

Usage

detect_irt_changepoints(
  data,
  person = "participant_id",
  order = "item_order",
  response = "response",
  rt = "rt",
  gaze = NULL,
  min_segment = 5L,
  min_delta_sic = 2,
  max_changes = 2L
)

Arguments

data

Input data frame or compatible tabular object.

person

Person or participant identifier column.

order

Within-sequence ordering variable.

response

Response variable or response-column name.

rt

Response-time variable or column name.

gaze

Gaze/process variable or column name.

min_segment

Minimum segment length.

min_delta_sic

Minimum information-criterion improvement.

max_changes

Maximum number of change points.