Agent modelling, statistical control, and the strength of middle knowledge

Fuente: arXiv
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Auteurs principaux: Chesney, Thomas, Gruchman, Tim, Pasley, Robert, Dawson, Altricia, Gold, Stefan
Format: Preprint
Publié: 2024
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author Chesney, Thomas
Gruchman, Tim
Pasley, Robert
Dawson, Altricia
Gold, Stefan
author_facet Chesney, Thomas
Gruchman, Tim
Pasley, Robert
Dawson, Altricia
Gold, Stefan
contents This methods article concerns analysing data generated from running experiments on agent based models to study industries and organisations. It demonstrates that when researchers study virtual ecologies they can and should discard statistical controls in favour of experiment controls. In the first of two illustrations we show that we can detect an effect with a fraction of the data needed for a traditional analysis, which is valuable given the computational complexity of many models. In the second we show that agent based models can provide control without introducing the biases associated with certain causal structures.
format Preprint
id arxiv_https___arxiv_org_abs_2409_17196
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Agent modelling, statistical control, and the strength of middle knowledge
Chesney, Thomas
Gruchman, Tim
Pasley, Robert
Dawson, Altricia
Gold, Stefan
Applications
This methods article concerns analysing data generated from running experiments on agent based models to study industries and organisations. It demonstrates that when researchers study virtual ecologies they can and should discard statistical controls in favour of experiment controls. In the first of two illustrations we show that we can detect an effect with a fraction of the data needed for a traditional analysis, which is valuable given the computational complexity of many models. In the second we show that agent based models can provide control without introducing the biases associated with certain causal structures.
title Agent modelling, statistical control, and the strength of middle knowledge
topic Applications
url https://arxiv.org/abs/2409.17196