code: def crossed_data():
      """
      Group specific effects:
      10 subjects, 12 items, 5 sites
      Subjects crossed with items, nested in sites
      Items crossed with sites
  
      Common effects:
      A continuous predictor, a numeric dummy, and a three-level category
      (levels a,b,c)
  
      Structure:
      Subjects nested in dummy (e.g., gender), crossed with threecats
      Items crossed with dummy, nested in threecats
      Sites partially crossed with dummy (4/5 see a single dummy, 1/5 sees both
      dummies)
      Sites crossed with threecats
      """
      data_dir = join(dirname(__file__), "data")
      data = pd.read_csv(join(data_dir, "crossed_random.csv"))
      return data
  
imports: import logging
  from functools import reduce
  from operator import add
  from os.path import dirname, join
  import arviz
  import numpy
  import pandas
  import pymc
  import pytest
  from formulae import design_matrices
  import bambi
  from bambi.terms import CommonTerm, GroupSpecificTerm
label_desc: Use image node_id 3 for calling a global function with example usage: crossed_data() and returns: data