DataGenerationForCausalInference

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Name of Quantlet: DataGenerationForCausalInference

Published in: Masterthesis 'Causal Inference using Machine Learning

Description: Generates synthetic data in form of a partial linear model to apply simulations for causal inference estimation. The parameter of interest is the treatment or uplift effect for a binary treatment assignment.

Keywords: synthetic data, causal inference, simulation, data generation, partial linear model, treatment effect, uplift, high-dimensional

Author: Daniel Jacob

Submitted: 2018/08/24

Output: 
- Partial linear Model
- Output variable (continuous)
- Treatment paramter (different options)
- Treatment assignment (binary)
- Covariates

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