# The general Nature of Saturated Designs

## TL;DR

This paper explores the properties and selection criteria of saturated designs in factorial experiments, focusing on how to retain information on significant effects when resources are limited and some effects are presumed negligible.

## Contribution

It provides a theoretical analysis of the flexibility in choosing saturated designs to preserve information on important effects in resource-constrained factorial experiments.

## Key findings

- Saturated designs can be flexibly chosen to retain key effect information.
- Pre-knowledge of negligible effects guides optimal design selection.
- The study offers insights into design choices under resource constraints.

## Abstract

We contemplate an experimental situation in a $2^k$-factorial experiment with acute resource crunch so that we need to conduct just a saturated design [SD] - with the understanding that precision of the estimates cannot be estimated from the data. It is known beforehand which effect(s)/interaction(s) are likely to be negligible. We examine the flexibility to the extent that an experimenter can make a choice of an SD in order to retain information on all the remaining [non-negligible] effects/interactions.