# Examples Gallery

This gallery showcases various examples demonstrating the capabilities of CausalLib.
Each example is a Jupyter notebook that you can view, download, and run locally.

```{eval-rst}
.. toctree::
   :maxdepth: 1
   :hidden:

   ipw
   standardization
   doubly_robust
   TMLE
   rlearner
   xlearner
   causal_survival_analysis
   matching
   matching_with_custom_backends
   lalonde_matching
   hemm_demo
   positivity
   evaluation_plots_overview
   causal_inference_vs_descriptive_statistics
   Bank-Marketing
   Dehejia_Wahba_replication
   nhefs
   MANAGE agricultural data
   fast_food_employment_card_krueger
   lalonde
   causal_simulator
```

---

## Models and Features

::::{grid} 1 1 2 2
:gutter: 3

:::{grid-item-card} Inverse Probability Weighting Model
:link: ipw
:link-type: doc

Inverse probability weighting is a basic model to obtain average effect estimation.
:::

:::{grid-item-card} Direct Outcome Prediction Model
:link: standardization
:link-type: doc

Also known as standardization
:::

:::{grid-item-card} Doubly Robust Models
:link: doubly_robust
:link-type: doc

Basically, different ensemble models that utilize a weight model to augment the outcome model.
:::

:::{grid-item-card} TMLE - Targeted Maximum Likelihood Estimation
:link: TMLE
:link-type: doc

Targeted learning is a method developed by Mark van der Laan [[1](https://www.degruyter.com/document/doi/10.2202/1557-4679.1043/html)] establishing...
:::

:::{grid-item-card} R-Learner
:link: rlearner
:link-type: doc

R-Learner provides a general framework for estimating causal effects using Machine Learning (ML) algorithms.
:::

:::{grid-item-card} X-learner
:link: xlearner
:link-type: doc

X-learner is a Meta-algorithm by [künzel et al. (2018)](https://www.pnas.org/content/116/10/4156)
:::

:::{grid-item-card} Causal Survival Analysis
:link: causal_survival_analysis
:link-type: doc

The modules under `causallib.estimation` estimate treatment effect on outcomes that are measured at a particular time point (e.g., effect of smokin...
:::

:::{grid-item-card} Matching Model
:link: matching
:link-type: doc

To find the expected effect of the intervention on the population, we match each treated individual with one or more untreated individuals which ar...
:::

:::{grid-item-card} Matching with Custom Backends
:link: matching_with_custom_backends
:link-type: doc

When performing matching on a sample set, we may want to use non-standard distance measurements or faster implementations. The default behavior is ...
:::

:::{grid-item-card} LaLonde Dataset
:link: lalonde_matching
:link-type: doc

Economists have long-hypothesized that training programs could improve the labor market prospects of participants.
:::

:::{grid-item-card} Heterogenous Effect Mixture Model (HEMM) Demo
:link: hemm_demo
:link-type: doc

:::

:::{grid-item-card} Positivity filtering
:link: positivity
:link-type: doc

This Notebooks presents several models that perform overlap exclusion
:::

:::{grid-item-card} An overview of `causallib` evaluation plots
:link: evaluation_plots_overview
:link-type: doc

To make it easier to assess the quality of the causal models, `causallib` supplies a number of evaluation plots.
:::

::::

## Real-World Use Cases

::::{grid} 1 1 2 2
:gutter: 3

:::{grid-item-card} Why Causal Analysis is Needed
:link: causal_inference_vs_descriptive_statistics
:link-type: doc

In this example we will perform a quick causal analysis to estimate the _causal effect_ of smoking cessation on weight gain over a period of a decade.
:::

:::{grid-item-card} The Effects of Marketing Decisions using the Bank Marketing Dataset
:link: Bank-Marketing
:link-type: doc

:::

:::{grid-item-card} LaLonde Dataset
:link: Dehejia_Wahba_replication
:link-type: doc

Economists have long-hypothesized that training programs could improve the labor market prospects of participants.
:::

:::{grid-item-card} NHEFS Dataset
:link: nhefs
:link-type: doc

**NHANS (National Health and Nutrition Examionation Survey) Epidemiologic Followup Study**
:::

:::{grid-item-card} Estimating the effect of agricultural conservation practices (CP) on reducing nutrient loss
:link: MANAGE agricultural data
:link-type: doc

We will use the Measured Annual Nutrient loads from AGricultural Environments (MANAGE) data from the USDA,
:::

:::{grid-item-card} Comparing Effect Estimators on Fast-food Employment Data
:link: fast_food_employment_card_krueger
:link-type: doc

We look at the famous Card and Krueger study[1] of the impact of a minimum wage change on employment levels in fast food restaurants near the borde...
:::

:::{grid-item-card} LaLonde Dataset
:link: lalonde
:link-type: doc

Economists have long-hypothesized that training programs could improve the labor market prospects of participants.
:::

:::{grid-item-card} Running a simulator using existing data
:link: causal_simulator
:link-type: doc

Consider the case when input data already exists, and that data already has a causal structure.
:::

::::