# {py:mod}`causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity`

```{py:module} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity
```

```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity
:allowtitles:
```

## Module Contents

### Functions

````{list-table}
:class: autosummary longtable
:align: left

* - {py:obj}`compute_sensitivity_bias <causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.compute_sensitivity_bias>`
  - ```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.compute_sensitivity_bias
    :summary:
    ```
* - {py:obj}`compute_sensitivity_bias_local <causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.compute_sensitivity_bias_local>`
  - ```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.compute_sensitivity_bias_local
    :summary:
    ```
* - {py:obj}`combine_nu2 <causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.combine_nu2>`
  - ```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.combine_nu2
    :summary:
    ```
* - {py:obj}`pulltheta_se_ci <causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.pulltheta_se_ci>`
  - ```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.pulltheta_se_ci
    :summary:
    ```
* - {py:obj}`compute_bias_aware_ci <causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.compute_bias_aware_ci>`
  - ```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.compute_bias_aware_ci
    :summary:
    ```
* - {py:obj}`format_bias_aware_summary <causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.format_bias_aware_summary>`
  - ```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.format_bias_aware_summary
    :summary:
    ```
* - {py:obj}`get_sensitivity_summary <causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.get_sensitivity_summary>`
  - ```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.get_sensitivity_summary
    :summary:
    ```
* - {py:obj}`sensitivity_benchmark <causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.sensitivity_benchmark>`
  - ```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.sensitivity_benchmark
    :summary:
    ```
* - {py:obj}`sensitivity_analysis <causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.sensitivity_analysis>`
  - ```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.sensitivity_analysis
    :summary:
    ```
````

### Data

````{list-table}
:class: autosummary longtable
:align: left

* - {py:obj}`__all__ <causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.__all__>`
  - ```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.__all__
    :summary:
    ```
````

### API

````{py:data} __all__
:canonical: causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.__all__
:value: >
   ['sensitivity_analysis', 'get_sensitivity_summary', 'sensitivity_benchmark', 'compute_bias_aware_ci'...

```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.__all__
```

````

````{py:function} compute_sensitivity_bias(sigma2: typing.Union[float, numpy.ndarray], nu2: typing.Union[float, numpy.ndarray], psi_sigma2: numpy.ndarray, psi_nu2: numpy.ndarray) -> typing.Tuple[numpy.ndarray, numpy.ndarray]
:canonical: causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.compute_sensitivity_bias

```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.compute_sensitivity_bias
```
````

````{py:function} compute_sensitivity_bias_local(sigma2: typing.Union[float, numpy.ndarray], nu2: typing.Union[float, numpy.ndarray], psi_sigma2: numpy.ndarray, psi_nu2: numpy.ndarray) -> typing.Tuple[numpy.ndarray, numpy.ndarray]
:canonical: causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.compute_sensitivity_bias_local

```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.compute_sensitivity_bias_local
```
````

````{py:function} combine_nu2(m_alpha: numpy.ndarray, rr: numpy.ndarray, cf_y: float, r2_d: typing.Union[float, numpy.ndarray], rho: typing.Union[float, numpy.ndarray], use_signed_rr: bool = False) -> typing.Tuple[typing.Union[float, numpy.ndarray], numpy.ndarray]
:canonical: causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.combine_nu2

```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.combine_nu2
```
````

````{py:function} pulltheta_se_ci(effect_estimation: typing.Any, alpha: float) -> typing.Tuple[typing.Union[float, numpy.ndarray], typing.Union[float, numpy.ndarray], typing.Union[typing.Tuple[float, float], numpy.ndarray]]
:canonical: causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.pulltheta_se_ci

```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.pulltheta_se_ci
```
````

````{py:function} compute_bias_aware_ci(effect_estimation: typing.Dict[str, typing.Any] | typing.Any, _=None, cf_y: float = 0.0, r2_d: typing.Union[float, numpy.ndarray] = 0.0, rho: typing.Union[float, numpy.ndarray] = 1.0, H0: float = 0.0, alpha: float = 0.05, use_signed_rr: bool = False) -> typing.Dict[str, typing.Any]
:canonical: causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.compute_bias_aware_ci

```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.compute_bias_aware_ci
```
````

````{py:function} format_bias_aware_summary(res: typing.Dict[str, typing.Any], label: str | None = None) -> str
:canonical: causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.format_bias_aware_summary

```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.format_bias_aware_summary
```
````

````{py:function} get_sensitivity_summary(effect_estimation: typing.Dict[str, typing.Any] | typing.Any, _=None, label: typing.Optional[str] = None) -> typing.Optional[str]
:canonical: causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.get_sensitivity_summary

```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.get_sensitivity_summary
```
````

````{py:function} sensitivity_benchmark(effect_estimation: typing.Dict[str, typing.Any] | typing.Any, benchmarking_set: typing.List[str], fit_args: typing.Optional[typing.Dict[str, typing.Any]] = None) -> pandas.DataFrame
:canonical: causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.sensitivity_benchmark

```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.sensitivity_benchmark
```
````

````{py:function} sensitivity_analysis(effect_estimation: typing.Dict[str, typing.Any] | typing.Any, _=None, cf_y: typing.Optional[float] = None, r2_y: typing.Optional[float] = None, r2_d: typing.Union[float, numpy.ndarray] = 0.0, rho: typing.Union[float, numpy.ndarray] = 1.0, H0: float = 0.0, alpha: float = 0.05, use_signed_rr: bool = False) -> typing.Dict[str, typing.Any]
:canonical: causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.sensitivity_analysis

```{autodoc2-docstring} causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.sensitivity.sensitivity_analysis
```
````
