# Workflow

## Workflow:

**This workflow can be captured by four key verbs in DoWhy:**

* model - encodes prior knowledge as a formal causal graph
* identify - uses graph-based methods to identify the causal effect
* estimate - uses statistical methods for estimating the identified estimand
* refute - tries to refute the obtained estimate by testing robustness to assumptions

## **Different estimation methods:**

1. **Regression:** Linear Regression Method used
2. **Stratification:** Propensity Score used for Stratification
3. **Matching:** Propensity Score used for Matching
4. **Weighting:**  Inverse Propensity Scoring technique used to assign weights to units
   1. Vanilla Inverse Propensity Score weighting (IPS) (weighting\_scheme=“ips\_weight”) 
   2. Self-normalized IPS weighting (also known as the Hajek estimator) (weighting\_scheme=“ips\_normalized\_weight”) 
   3. Stabilized IPS weighting (weighting\_scheme = “ips\_stabilized\_weight”)
5. **Instrumental Variable** - Wald estimator used
6. **Regression Discontinuity**

Go to the [Notebook](https://github.com/abhishekdabas31/Causal-Inference-implementation/tree/master/DoWhy) for **reference**!!