Generalised linear model trees with global additive effects
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DOI: 10.1007/s11634-018-0342-1
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- L. Doove & E. Dusseldorp & K. Deun & I. Mechelen, 2014. "A comparison of five recursive partitioning methods to find person subgroups involved in meaningful treatment–subgroup interactions," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(4), pages 403-425, December.
- Hajjem, Ahlem & Bellavance, François & Larocque, Denis, 2011. "Mixed effects regression trees for clustered data," Statistics & Probability Letters, Elsevier, vol. 81(4), pages 451-459, April.
- Achim Zeileis & Kurt Hornik, 2007. "Generalized M‐fluctuation tests for parameter instability," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 61(4), pages 488-508, November.
- Lawrence Hubert & Phipps Arabie, 1985. "Comparing partitions," Journal of Classification, Springer;The Classification Society, vol. 2(1), pages 193-218, December.
- Seibold Heidi & Zeileis Achim & Hothorn Torsten, 2016. "Model-Based Recursive Partitioning for Subgroup Analyses," The International Journal of Biostatistics, De Gruyter, vol. 12(1), pages 45-63, May.
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Cited by:
- Manlio Migliorati & Marica Manisera & Paola Zuccolotto, 2023. "Integration of model-based recursive partitioning with bias reduction estimation: a case study assessing the impact of Oliver’s four factors on the probability of winning a basketball game," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 271-293, March.
- Anna Gottard & Giulia Vannucci & Leonardo Grilli & Carla Rampichini, 2023. "Mixed-effect models with trees," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(2), pages 431-461, June.
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Keywords
Subgroup analysis; Model-based recursive partitioning; GLM; Tree;All these keywords.
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