A likelihood-based approach for multivariate one-sided tests with missing data

DOI10.1080/02664763.2016.1238054OpenAlexW2528587226WikidataQ58876110 ScholiaQ58876110MaRDI QIDQ5138684

Rollin Brant, J Mark Ansermino, Guohai Zhou, Lang Wu

Publication date: 4 December 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://figshare.com/articles/journal_contribution/A_likelihood-based_approach_for_multivariate_one-sided_tests_with_missing_data/3984494

zbMATH Keywords

longitudinal datamissing datamultivariate datalikelihood methodinequality-restricted inference

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• BOBYQA

Cites Work

• Tests of homoscedasticity, normality, and missing completely at random for incomplete multivariate data
• Accuracy of Laplace approximation for discrete response mixed models
• Multivariate one-sided tests for nonlinear mixed-effects models
• Testing for generalized linear mixed models with cluster correlated data under linear inequality constraints
• Multiple Imputation Methods for Multivariate One-Sided Tests with Missing Data
• Constrained inference in mixed-effects models for longitudinal data with application to hearing loss
• Mixed Effects Models for Complex Data
• Asymptotic Properties of Maximum Likelihood Estimators and Likelihood Ratio Tests Under Nonstandard Conditions
• Inference and missing data
• One-Sided Testing Problems in Multivariate Analysis
• On the Distribution of the Likelihood Ratio

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