Evaluation of four multiple imputation methods for handling missing binary outcome data in the presence of an interaction between a dummy and a continuous variable

DOI10.1155/2021/6668822zbMath1468.62255OpenAlexW3162850844MaRDI QIDQ2039155

Mohammad Mehdi Saber, Mohammad Reza Baneshi, Abbas Bahrampour, Behshid Garrusi, Sara Javadi

Publication date: 2 July 2021

Published in: Journal of Probability and Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2021/6668822

zbMATH Keywords

MCAR (missing completely at random)missing binary outcome data

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Missing data (62D10)

Uses Software

• Stata
• rpart
• MICE
• mi
• randomForest
• ElemStatLearn
• ice

Cites Work

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• Problems in the Analysis of Survey Data, and a Proposal
• The elements of statistical learning. Data mining, inference, and prediction

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