QteResult

cross_sectional.QteResult(
    qtt: pl.DataFrame,
    att: pl.DataFrame,
    outcome: ColumnName,
    group: tuple[str] | tuple[str, str] | None,
    estimator: Estimator,
    causal_target: CausalTarget,
    propensity_score_formula: FormulaRhs | None = None,
    outcome_regression_formula: FormulaRhs | None = None,
)

Result of a cross-sectional quantile treatment effect estimation.

Use plot, tabulate, summarize or get_as_dataframe to present the estimates. Instances are returned by the estimate_* functions; the constructor is not part of the public API.

Attributes

Name	Type	Description
qtt	`polars`.`DataFrame`	Quantile-specific effects, one row per quantile.
att	`polars`.`DataFrame`	Average treatment effects.
outcome	`ColumnName`	Outcome variable the effect was estimated for.
group	`tuple`[`str`, …] or None	Columns the estimates are grouped by.
estimator	`Estimator`	Estimator that produced the result.
causal_target	`CausalTarget`	Estimand that was targeted.
propensity_score_formula	(`FormulaRhs`, `optional`)	Propensity score formula, when applicable.
outcome_regression_formula	(`FormulaRhs`, `optional`)	Outcome regression formula, when applicable.

Methods

Name	Description
get_as_dataframe	Return the quantile effects with confidence interval columns.
plot	Plot the quantile and average effects with confidence intervals.
summarize	Render a rich text summary of the estimates.
tabulate	Build a Great Tables table of the estimates.

get_as_dataframe

cross_sectional.QteResult.get_as_dataframe(alpha: float = 0.95)

Return the quantile effects with confidence interval columns.

Parameters

Name	Type	Description	Default
alpha	`float`	Confidence level of the intervals.	`0.95`

Returns

Name	Type	Description
	`polars`.`DataFrame`	Quantile effects with `ci_lb` and `ci_ub` columns.

plot

cross_sectional.QteResult.plot(alpha: float = 0.95)

Plot the quantile and average effects with confidence intervals.

Parameters

Name	Type	Description	Default
alpha	`float`	Confidence level of the intervals.	`0.95`

Returns

Name	Type	Description
	`altair`.`Chart`	Altair chart of the estimates.

summarize

cross_sectional.QteResult.summarize(alpha: float = 0.95)

Render a rich text summary of the estimates.

Parameters

Name	Type	Description	Default
alpha	`float`	Confidence level of the intervals.	`0.95`

Returns

Name	Type	Description
	`rich`.`console`.`Group`	Rich renderable for terminals and notebooks.

tabulate

cross_sectional.QteResult.tabulate(alpha: float = 0.95)

Build a Great Tables table of the estimates.

Parameters

Name	Type	Description	Default
alpha	`float`	Confidence level of the intervals.	`0.95`

Returns

Name	Type	Description
	`great_tables`.`GT`	Formatted table of the estimates.