Unbiased regression trees for longitudinal and clustered data

DOI10.1016/J.CSDA.2015.02.004zbMath1468.62058OpenAlexW1984622488MaRDI QIDQ1663279

Wei Fu, Jeffrey S. Simonoff

Publication date: 21 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2015.02.004

zbMATH Keywords

longitudinal dataclustered datamixed modelsregression tree

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (6)

On missing random effects in machine learning ⋮ A Lasso and a regression tree mixed-effect model with random effects for the level, the residual variance, and the autocorrelation ⋮ Generalized mixed effects regression trees ⋮ Mixed-effect models with trees ⋮ Predictions of machine learning with mixed-effects in analyzing longitudinal data under model misspecification ⋮ Analysis of web visit histories. II: Predicting navigation by nested STUMP regression trees

Cites Work

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• RE-EM trees: a data mining approach for longitudinal and clustered data
• Random-Effects Models for Longitudinal Data
• Mixed effects regression trees for clustered data
• Bias in information-based measures in decision tree induction
• The asymptotic theory of permutation statistics.
• Regression trees for longitudinal and multiresponse data
• Classification Trees for Multiple Binary Responses
• Regression tree-based diagnostics for linear multilevel models

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