A Comparison of Multilevel Imputation Schemes for Random Coefficient Models: Fully Conditional Specification and Joint Model Imputation with Random Covariance Matrices Article

Enders, Craig K, Hayes, Timothy, Du, Han. (2018). A Comparison of Multilevel Imputation Schemes for Random Coefficient Models: Fully Conditional Specification and Joint Model Imputation with Random Covariance Matrices . 53(5), 695-713. 10.1080/00273171.2018.1477040

Open Access

cited authors

  • Enders, Craig K; Hayes, Timothy; Du, Han

sustainable development goals

authors

publication date

  • September 3, 2018

keywords

  • IMPACT
  • INTRACLASS CORRELATION
  • LIKELIHOOD
  • LINEAR-MODELS
  • MISSING-DATA
  • MIXED-EFFECTS MODELS
  • MULTIPLE-IMPUTATION
  • Mathematical Methods In Social Sciences
  • Mathematics
  • Mathematics, Interdisciplinary Applications
  • Missing data
  • OUTCOMES
  • Physical Sciences
  • Psychology
  • Psychology, Experimental
  • STRATEGIES
  • Science & Technology
  • Social Sciences
  • Social Sciences, Mathematical Methods
  • Statistics & Probability
  • VALUES
  • fully conditional specification
  • joint model imputation
  • multilevel models
  • multiple imputation

Digital Object Identifier (DOI)

publisher

  • ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD

start page

  • 695

end page

  • 713

volume

  • 53

issue

  • 5