SUPR
Experimental designs for causal effects
Dnr:

NAISS 2025/22-929

Type:

NAISS Small Compute

Principal Investigator:

Fredrik Sävje

Affiliation:

Uppsala universitet

Start Date:

2025-07-01

End Date:

2026-07-01

Primary Classification:

10106: Probability Theory and Statistics (Statistics with medical aspects at 30118 and with social aspects at 50907)

Allocation

Abstract

Randomized experiments assign causal factors (or treatments) under study at random to the units in an experiment sample. This facilitates investigation of causal effects without strong assumptions, which has made the method the gold standard in causal inference in many fields in the social and medical sciences. This project aims to investigate what probability distributions (typically called experimental designs) to use when drawing the randomized treatments. The cluster will be used primarily for Monte Carlo investigations of various designs.