Subgroup analysis for longitudinal data via semiparametric additive mixed effects model

Nonparametric regression and quantile regression (62G08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

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RE-EM trees: a data mining approach for longitudinal and clustered data
Bayesian identification, selection and estimation of semiparametric functions in high-dimensional additive models
Structure identification in panel data analysis
Generalized \(k\)-means in GLMs with applications to the outbreak of COVID-19 in the United States
High-dimensional additive modeling
Estimating the dimension of a model
A practical guide to splines
Clustering longitudinal profiles using P-splines and mixed effects models applied to time-course gene expression data
Consistency of AIC and BIC in estimating the number of significant components in high-dimensional principal component analysis
Cluster analysis of longitudinal profiles with subgroups
Local asymptotics for regression splines and confidence regions
Higher criticism for detecting sparse heterogeneous mixtures.
Regression trees for longitudinal and multiresponse data
Hierarchical clustering schemes
Abstraction and pattern classification
KmL: k-means for longitudinal data
Model-based clustering
Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Additive Models
On the asymptotics of marginal regression splines with longitudinal data
Efficient Estimation in Marginal Partially Linear Models for Longitudinal/Clustered Data Using Splines
Modeling Longitudinal Data with Nonparametric Multiplicative Random Effects Jointly with Survival Data
Model‐based clustering of longitudinal data
Moment inequalities for mixing sequences of random variables
Unsupervised Curve Clustering using B‐Splines
Model-Based Clustering, Discriminant Analysis, and Density Estimation
Nonparametric Cluster Analysis on Multiple Outcomes of Longitudinal Data
Discrete Longitudinal Data Modeling with a Mean-Correlation Regression Approach
ROBUST SUBGROUP IDENTIFICATION
Regularization Parameter Selections via Generalized Information Criterion
A new approach to clustering
Homogeneity Pursuit in Single Index Models based Panel Data Analysis
Homogeneity and Structure Identification in Semiparametric Factor Models
Subgroup identification via homogeneity pursuit for dense longitudinal/spatial data
Model-based recursive partitioning for subgroup analyses

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