# On Randomization-based and Regression-based Inferences for 2^K Factorial Designs

arXiv: https://arxiv.org/abs/1602.03972 · HTML: https://mlsanity.com/paper/1602.03972/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Feb 2016.

## Built on by (most cited first, 1 of 1)

- [Beyond Accuracy: How Humans Evaluate Legally Correct but Socially Controversial Legal Advice from Machines](https://mlsanity.com/paper/2607.05680/) (2026)

## Abstract (arXiv)

We extend the randomization-based causal inference framework in Dasgupta et al. (2015) for general 2^K factorial designs, and demonstrate the equivalence between regression-based and randomization-based inferences. Consequently, we justify the use of regression-based methods in 2^K factorial designs from a finite-population perspective.