Hypothesis Testing in Multivariate Linear Models with Randomly Missing Data

DOI10.1080/03610918908812796zbMath0695.62160OpenAlexW2065470934MaRDI QIDQ3471504

Elliot C. Cramer, Curtis N. Barton

Publication date: 1989

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918908812796

zbMATH Keywords

EM algorithmincomplete datatype I errorempirical powers

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Hypothesis testing in multivariate analysis (62H15)

Related Items (2)

On the distribution of summary statistics for missing data ⋮ Power for balanced linear mixed models with complex missing data processes

Cites Work

• Practical methods for computing power in testing the multivariate general linear hypothesis
• A generalization of the growth curve model which allows missing data
• Multivariate data with missing observations
• Testing hypotheses for the growth curve model when the data are incomplete
• A monte carlo investigation of a statistic for a bivariate missing data problem
• On comparing means in the paired case with incomplete data on both responses
• Inference and missing data
• Testing equality of means of correlated variates with missing observations on both responses
• On difference of means with incomplete data

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