Multiple Imputation Methods for Multivariate One-Sided Tests with Missing Data

DOI10.1111/j.1541-0420.2011.01597.xzbMath1274.62898OpenAlexW2052457798WikidataQ33863176 ScholiaQ33863176MaRDI QIDQ2893406

Lang Wu, Tao Wang

Publication date: 20 June 2012

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1541-0420.2011.01597.x

zbMATH Keywords

multiple imputationorder-restricted inferenceconstrained inferenceWald-type tests

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Hypothesis testing in multivariate analysis (62H15)

Related Items (3)

A likelihood-based approach for multivariate one-sided tests with missing data ⋮ A Multiple Imputation Approach for the Evaluation of Surrogate Markers in the Principal Stratification Causal Inference Framework ⋮ Multivariate one-sided tests for nonlinear mixed-effects models

Cites Work

• Unnamed Item
• Some improved tests for multivariate one-sided hypotheses
• Multiple Imputation After 18+ Years
• Performing likelihood ratio tests with multiply-imputed data sets
• One-Sided Testing Problems in Multivariate Analysis

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