Study planning is better served by Monte Carlo simulation than AI-generated participants

Abstract excerpt

<p>'Silicon samples' – synthetic data generated by large language models prompted with demographic profiles – have been proposed as a useful method for planning human subjects research by providing useful effect size estimates. Monte Carlo simulation addresses the same planning problem from the opposite direction: the researcher specifies a data-generating process, then asks what follows. Monte Carlo simulation th...

Topics

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• Algorithms
• Bayes Theorem
• Genomics
• Markov Chains
• Metabolic Syndrome
• Models, Statistical
• Monte Carlo Method
• Stochastic Processes

Identifiers and source

Literature Corpus work

e101bf56-7465-5b70-9740-5eec97841a1d

DOI

10.31234/osf.io/jw9gz_v1