Function generate_crossed

examples/python/variance_components.py:131–161

(n_group1=100,
                     n_group2=100,
                     n_rep=4,
                     group1_sd=2,
                     group2_sd=3,
                     unexplained_sd=4)

def generate_crossed(n_group1=100,
                     n_group2=100,
                     n_rep=4,
                     group1_sd=2,
                     group2_sd=3,
                     unexplained_sd=4):

    # Group 1 indicators
    group1 = np.kron(np.arange(n_group1, dtype=int),
                     np.ones(n_group2 * n_rep, dtype=int))
    group1 = group1[np.random.permutation(len(group1))]

    # Group 1 effects
    u = group1_sd * np.random.normal(size=n_group1)
    effects1 = u[group1]

    # Group 2 indicators
    group2 = np.kron(np.arange(n_group2, dtype=int),
                     np.ones(n_group2 * n_rep, dtype=int))
    group2 = group2[np.random.permutation(len(group2))]

    # Group 2 effects
    u = group2_sd * np.random.normal(size=n_group2)
    effects2 = u[group2]

    e = unexplained_sd * np.random.normal(size=n_group1 * n_group2 * n_rep)
    y = effects1 + effects2 + e

    df = pd.DataFrame({"y": y, "group1": group1, "group2": group2})

    return df


# Generate a data set to analyze.