Organize data for estimation (internal helper) — organize

Prepares tidy inputs for MM/AMCE estimation and IRR handling. Called inside pj_estimate() after reshaping to respondent–task–profile.

Usage

organize_data(
  .dataframe,
  .structure,
  .estimand,
  .remove_ties,
  .att_choose,
  .lev_choose,
  .att_notchoose,
  .lev_notchoose
)

.dataframe: A tibble/data frame from reshape_projoint(), containing columns like id, task, profile, selected, agree (if repeated), and attribute columns named att1, att2, ... that store level_ids (e.g., "att1:level2").
.structure: Either "profile_level" or "choice_level".
.estimand: Either "mm" or "amce".
.remove_ties: Logical; if TRUE (default) remove tied responses in profile-level setups (keeps tasks where exactly one profile is selected).
.att_choose: Attribute ID for the “chosen” side (e.g., "att3").
.lev_choose: Level ID(s) for the chosen side (e.g., "level2" for profile-level; vector of level IDs for choice-level).
.att_notchoose: Attribute ID for the “not chosen” side (choice-level only).
.lev_notchoose: Level ID(s) for the not-chosen side (choice-level only).

A named list with two tibbles:

$data_for_estimand: rows restricted and reshaped to the requested estimand/QOI. For profile-level, one row per respondent–task–profile where the target level is present (ties optionally removed). For choice-level, one row per respondent–task with paired information for profiles 1 and 2, restricted to the requested attribute-level pair(s).
$data_for_irr: one row per respondent with columns id, agree (if available), and any detected weight/cluster hints (columns matching "my_weight|my_cluster|^weights?$|^clusters?$").