def is_higher_order(e1, e0):
"""
Returns True if e1 is a higher order term of e0 (i.e., all factors in e0
are contained in e1).
e1, e0 : effects
The effects to compare.
"""
f1s = find_factors(e1)
return all(f in f1s for f in find_factors(e0))
def _hopkins_test(e, e2):
"""
Tests whether e2 is in the E(MS) of e.
e : effect
effect whose E(MS) is being constructed
e2 : effect
model effect which is tested for inclusion in E(MS) of e
"""
if e is e2:
return False
else:
e_factors = find_factors(e)
e2_factors = find_factors(e2)
a = np.all([(f in e_factors or f.random) for f in e2_factors])
b = np.all([(f in e2_factors or isnestedin(e2, f)) for f in e_factors])
return a and b