Bayesian decision theory for tree-based adaptive screening tests with an application to youth delinquency

DOI10.1214/22-aoas1657arXiv2106.10364OpenAlexW3174182781MaRDI QIDQ6104091

Yi Zheng, Chelsea Krantsevich, P. Richard Hahn, Charles Katz

Publication date: 5 June 2023

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2106.10364

zbMATH Keywords

computerized adaptive testingclassification treesrisk assessmentBayesian decision theoryrisk factorscomputerized adaptive diagnostics

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Cites Work

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• Variable selection in seemingly unrelated regressions with random predictors
• Item selection in multidimensional computerized adaptive testing-gaining information from different angles
• Post-processing posteriors over precision matrices to produce sparse graph estimates
• Psychometrics behind computerized adaptive testing
• An algorithm for removing sensitive information: application to race-independent recidivism prediction
• Decision Theory
• Log-Linear Bayesian Additive Regression Trees for Multinomial Logistic and Count Regression Models
• Model Interpretation Through Lower-Dimensional Posterior Summarization
• Bayesian Gaussian Copula Factor Models for Mixed Data
• Decoupling Shrinkage and Selection in Bayesian Linear Models: A Posterior Summary Perspective
• Random forests

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