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causalis
Package entry
causalisRoot package overview and namespace mapNamespaces
causalis.scenarios.iv.refutation.diagnosticsSubmodule causalis.scenarios.iv.refutation.diagnostics with no child pages and 8 documented members.
Functions
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Data
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causalis.scenarios.iv.refutation.diagnostics.compute_instrument_overlap_diagnosticsCompute instrument propensity/overlap diagnostics from IV diagnostic data.
Canonical target
causalis.scenarios.iv.refutation.diagnostics.compute_instrument_overlap_diagnostics
causalis.scenarios.iv.refutation.diagnostics.compute_first_stage_diagnosticsCompute controlled first-stage diagnostics: D ~ 1 + Z + X.
Canonical target
causalis.scenarios.iv.refutation.diagnostics.compute_first_stage_diagnostics
causalis.scenarios.iv.refutation.diagnostics.compute_reduced_form_diagnosticsCompute simple reduced-form diagnostics: Y ~ 1 + Z.
Canonical target
causalis.scenarios.iv.refutation.diagnostics.compute_reduced_form_diagnostics
causalis.scenarios.iv.refutation.diagnostics.instrument_overlapReturn instrument propensity/overlap diagnostics for an IV result.
Checks how well the instrument can be predicted from covariates and whether there is sufficient overlap in instrument assignment.
Parameters
The fitted IV model or its estimation result.
Returns
A table with diagnostic metrics (AUC, KS, ESS ratio).
Examples
Assuming ‘result’ is obtained from model.estimate()
Canonical target
causalis.scenarios.iv.refutation.diagnostics.instrument_overlap
Sections
causalis.scenarios.iv.refutation.diagnostics.first_stageReturn first-stage diagnostics for an IV result.
Checks the strength of the relationship between the instrument and the treatment. A weak first stage (F-statistic < 10 or similar) can lead to biased and unstable IV estimates.
Parameters
The fitted IV model or its estimation result.
Returns
A table with first-stage metrics (Effect, F-statistic, Partial R2, etc.).
Examples
Assuming ‘result’ is obtained from model.estimate()
Canonical target
causalis.scenarios.iv.refutation.diagnostics.first_stage
Sections
causalis.scenarios.iv.refutation.diagnostics.reduced_formReturn reduced-form sanity diagnostics for an IV result.
The reduced form is the regression of the outcome on the instrument.
Under the IV assumptions, the LATE is the ratio of the reduced-form
effect to the first-stage effect.
.. math::
heta =
rac{\mathbb{E}[Y|Z=1] - \mathbb{E}[Y|Z=0]}{\mathbb{E}[D|Z=1] - \mathbb{E}[D|Z=0]}
Parameters
----------
result : IIVM or IVCausalEstimate
The fitted IV model or its estimation result.
Returns
-------
pd.DataFrame
A table with reduced-form metrics.
Examples
--------
>>> from causalis.scenarios.iv.refutation import reduced_form
>>> # Assuming 'result' is obtained from model.estimate()
>>> reduced_form(result)
causalis.scenarios.iv.refutation.diagnostics.instrument_overlap_plotPlot instrument propensity distributions by observed instrument group.
Visualizes the overlap of P(Z=1∣X) between the Z=0 and Z=1 groups. Good overlap is essential for reliable IV estimation.
Parameters
The fitted IV model or its estimation result.
Binning strategy for histograms.
Pre-existing axes to plot on.
Figure size.
Resolution.
Path to save the figure.
Returns
The generated figure.
Canonical target
causalis.scenarios.iv.refutation.diagnostics.instrument_overlap_plot
Sections
causalis.scenarios.iv.refutation.diagnostics.__all__[‘compute_first_stage_diagnostics’, ‘compute_instrument_overlap_diagnostics’, ‘compute_reduced_form_…