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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "SBMTrees" in publications use:'
type: software
license: GPL-2.0-only
title: 'SBMTrees: Sequential Imputation with Bayesian Trees Mixed-Effects Models for
  Longitudinal Data'
version: '1.2'
doi: 10.32614/CRAN.package.SBMTrees
abstract: Implements a sequential imputation framework using Bayesian Mixed-Effects
  Trees ('SBMTrees') for handling missing data in longitudinal studies. The package
  supports a variety of models, including non-linear relationships and non-normal
  random effects and residuals, leveraging Dirichlet Process priors for increased
  flexibility. Key features include handling Missing at Random (MAR) longitudinal
  data, imputation of both covariates and outcomes, and generating posterior predictive
  samples for further analysis. The methodology is designed for applications in epidemiology,
  biostatistics, and other fields requiring robust handling of missing data in longitudinal
  settings.
authors:
- family-names: Zou
  given-names: Jungang
  email: jungang.zou@gmail.com
- family-names: Hu
  given-names: Liangyuan
repository: https://zjg540066169.r-universe.dev
commit: fa40fb295f9abb5a6dae09bbebbe43e437192b45
date-released: '2024-11-20'
contact:
- family-names: Zou
  given-names: Jungang
  email: jungang.zou@gmail.com