diff_diff.QUGTestResults#

class diff_diff.QUGTestResults[source]#

Bases: object

Result of qug_test() (paper Theorem 4).

The QUG test rejects H_0: d_lower = 0 when the order-statistic ratio T = D_{(1)} / (D_{(2)} - D_{(1)}) exceeds 1/alpha - 1. Under the null, the asymptotic limit law of T is the ratio of two independent Exp(1) random variables, with CDF F(t) = t / (1 + t), so p_value = 1 / (1 + T).

t_stat#

D_{(1)} / (D_{(2)} - D_{(1)}). NaN when fewer than 2 non-zero observations remain or when the two smallest doses tie.

Type:: float

p_value#

1 / (1 + t_stat) under the null. NaN when t_stat is NaN.

Type:: float

reject#

True iff t_stat > critical_value. False on NaN statistic.

Type:: bool

alpha#

Significance level used.

Type:: float

critical_value#

1 / alpha - 1. Populated even when the statistic is NaN so downstream readers can inspect the decision threshold.

Type:: float

n_obs#

Number of observations after filtering to d > 0.

Type:: int

n_excluded_zero#

Number of zero-dose observations excluded from the sample.

Type:: int

d_order_1#

Smallest positive dose D_{(1)}. NaN when n_obs < 2.

Type:: float

d_order_2#

Second-smallest positive dose D_{(2)}. NaN when n_obs < 2.

Type:: float

Methods

`__init__`(t_stat, p_value, reject, alpha, ...)
`print_summary`()	Print the summary to stdout.
`summary`()	Formatted summary table.
`to_dataframe`()	Return a one-row DataFrame of the result dict.
`to_dict`()	Return results as a JSON-safe dict.

Attributes

`t_stat`
`p_value`
`reject`
`alpha`
`critical_value`
`n_obs`
`n_excluded_zero`
`d_order_1`
`d_order_2`

__init__(t_stat, p_value, reject, alpha, critical_value, n_obs, n_excluded_zero, d_order_1, d_order_2)#

Parameters:

t_stat (float)
p_value (float)
reject (bool)
alpha (float)
critical_value (float)
n_obs (int)
n_excluded_zero (int)
d_order_1 (float)
d_order_2 (float)

Return type:

None

classmethod __new__(*args, **kwargs)#