diff_diff.PreTrendsPowerCurve

class diff_diff.PreTrendsPowerCurve[source]

Bases: object

Power curve across violation magnitudes.

M_values

Grid of violation magnitudes tested.

Type:

np.ndarray

powers

Power at each violation magnitude.

Type:

np.ndarray

mdv

Minimum detectable violation.

Type:

float

alpha

Significance level.

Type:

float

target_power

Target power level.

Type:

float

violation_type

Type of violation pattern.

Type:

str

__init__(M_values, powers, mdv, alpha, target_power, violation_type)
Parameters:
Return type:

None

Methods

__init__(M_values, powers, mdv, alpha, ...)

plot([ax, show_mdv, show_target, color, ...])

Plot the power curve.

to_dataframe()

Convert to DataFrame with M and power columns.

Attributes

M_values

powers

mdv

alpha

target_power

violation_type

M_values: ndarray
powers: ndarray
mdv: float
alpha: float
target_power: float
violation_type: str
to_dataframe()[source]

Convert to DataFrame with M and power columns.

Return type:

DataFrame

plot(ax=None, show_mdv=True, show_target=True, color='#2563eb', mdv_color='#dc2626', target_color='#22c55e', **kwargs)[source]

Plot the power curve.

Parameters:

  • ax (matplotlib.axes.Axes, optional) – Axes to plot on. If None, creates new figure.

  • show_mdv (bool, default=True) – Whether to show vertical line at MDV.

  • show_target (bool, default=True) – Whether to show horizontal line at target power.

  • color (str) – Color for power curve line.

  • mdv_color (str) – Color for MDV vertical line.

  • target_color (str) – Color for target power horizontal line.

  • **kwargs – Additional arguments passed to plt.plot().

Returns:

ax – The axes with the plot.

Return type:

matplotlib.axes.Axes

__init__(M_values, powers, mdv, alpha, target_power, violation_type)
Parameters:
Return type:

None