Mixed effectsPenalized quasi-likelihood algorithmEM-algorithmThis paper presents generalized mixed effects regression trees, an extension of mixed effects regression trees to other types of outcomes. A simulation shows that the proposed method provides substantial improvements over standard trees when data ...
The method of classification and regression trees ( CART ) is one approach to model the relationship between a classification, response or dependent variable to factors or independent variables possibly measured on different scales. The generalization of regression trees is defined via the additive ...
Conclusion: GLMM trees provide a useful data-analytic tool for clinical prediction problems. The supplemental material provides a tutorial for replicating the GLMM tree analyses in R. 展开 关键词: multilevel data decision making decision-tree methods mixed-effects models subgroup detection DOI: ...
A comparison of regression trees, logistic regression, generalized additive models, and multivariate adaptive regression splines for predicting AMI mortality Austin PC. A comparison of regression trees, logistic regression, generalized additive models, and multivariate adaptive regression splines for predicting...
In the second section, we compare the performance of GLMM trees with that of three other methods: MOB trees without random effects, mixed-effects regression trees (MERTs) and linear mixed-effects models with pre-specified interactions. In the third section, we apply the GLMM tree algorithm to...
Linear mixed-effects model fit by REML Data: Rail Log-restricted-likelihood: -61.0885 Fixed: travel ~ 1 (Intercept) 66.5 Random effects: Formula: ~1 | Rail (Intercept) Residual StdDev: 24.80547 4.020779 Number of Observations: 18 Number of Groups: 6 summary(rm) > summary(rm) Linear mixed-...
In a simulation study, GLMM trees show higher accuracy in recovering treatment-subgroup interactions, higher predictive accuracy, and lower type II error rates than linear-model-based recursive partitioning and mixed-effects regression trees. Also, GLMM trees show somewhat higher predictive accuracy than...
r machine-learning-algorithms statistical-learning datascience data-analysis logistic-regression regularization decision-trees predictive-modeling polynomial-regression clustering-algorithm svm-classifier k-nn boosting generalized-additive-models supervised-machine-learning bagging depth-interpretation discriminant-anlaysi...
Seeing the forest and the trees: multilevel models reveal both species and community patterns generalized linear mixed modelsmultilevel modelsordinationunderstory herbsSouthern Appalachian Mountains, USAspecies distributionsStudies designed to understand species ... MM Jackson,MG Turner,SM Pearson,... - 《...
either of parametric linear form or smoothing splines, or regression trees as base learners for fitting generalized linear, additive and interaction models to... T Hothorn,P Buhlmann - 《Bioinformatics》 被引量: 104发表: 2006年 Estimation of derivates for additive separable models Additive regressio...