Prediction and Inference With Missing Data in Patient Alert Systems
DOI10.1080/01621459.2019.1604359zbMath1437.62613arXiv1704.07904OpenAlexW2963126431WikidataQ128001790 ScholiaQ128001790MaRDI QIDQ3304829
Santiago Romero-Brufau, Jeanne M. Huddleston, John R. Bergquist, Terry M. Therneau, R. E. Carter, Curtis B. Storlie, Nicholas J. Y. Chia
Publication date: 3 August 2020
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1704.07904
Dirichlet processmissing datamultiple imputationlatent variablehierarchical Bayesian modelcontinuous and categorical
Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Sampling theory, sample surveys (62D05)
Related Items
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Greedy function approximation: A gradient boosting machine.
- A Bayesian analysis of the multinomial probit model using marginal data augmentation
- Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
- Tobit models: A survey
- Latent class based multiple imputation approach for missing categorical data
- Bayesian analysis of multivariate nominal measures using multivariate multinomial probit models
- A Bayesian analysis of the multinomial probit model with fully identified parameters
- Bayesian multivariate mixed-scale density estimation
- A Bayesian analysis of some nonparametric problems
- Efficient estimation of covariance selection models
- Variable selection in clustering via Dirichlet process mixture models
- Fully conditional specification in multivariate imputation
- Every Missingness not at Random Model Has a Missingness at Random Counterpart with Equal Fit
- Kernel stick-breaking processes
- Bayesian curve fitting using multivariate normal mixtures
- Existence and Uniqueness of the Maximum Likelihood Estimator for a Multivariate Probit Model
- Inference and missing data
- The Efficiency of Cox's Likelihood Function for Censored Data
- Analysis of multivariate probit models
- A conditional model for incomplete covariates in parametric regression models
- A Correlated Probit Model for Joint Modeling of Clustered Binary and Continuous Responses
- Gibbs Sampling Methods for Stick-Breaking Priors
- Simplex Factor Models for Multivariate Unordered Categorical Data
- Decomposable graphical Gaussian model determination
- A Potential for Bias When Rounding in Multiple Imputation
- A Bayesian Reliability Analysis of Neutron-Induced Errors in High Performance Computing Hardware
- Variable Selection for Model-Based Clustering
