Small-sample adjustments to tests with unbalanced repeated measures assuming several covariance structures

DOI10.1080/00949659008811295zbMath0775.62177OpenAlexW2001603349MaRDI QIDQ3135421

Mark D. Schluchter, Janet D. Elashoff

Publication date: 7 October 1993

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949659008811295

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Point estimation (62F10) Linear inference, regression (62J99) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (7)

Alternatives to the usual likelihood ratio test in mixed linear models ⋮ Wald-type rank tests: a GEE approach ⋮ A unified approach to rank tests for mixed models ⋮ Practical Review and Comparison of Modified Covariance Estimators for Linear Mixed Models in Small‐sample Longitudinal Studies with Missing Data ⋮ On analysis of binary response data in longitudinal factorial studies ⋮ Use of between-within degrees of freedom as an alternative to the Kenward–Roger method for small-sample inference in generalized linear mixed modeling of clustered count data ⋮ Small sample inference for the fixed effects in the mixed linear model

Uses Software

• BMDP

Cites Work

• Random-Effects Models for Longitudinal Data
• Unbalanced Repeated-Measures Models with Structured Covariance Matrices
• A monte carlo study of alternative procedures for testing the hypothesis of parallelism for complete and incomplete growth curve data
• Two-Stage Analysis Based on a Mixed Model: Large-Sample Asymptotic Theory and Small-Sample Simulation Results
• Testing hypotheses for the growth curve model when the data are incomplete
• Maximum Likelihood Computations with Repeated Measures: Application of the EM Algorithm
• Bayesian inference for variance components using only error contrasts
• A generalized multivariate analysis of variance model useful especially for growth curve problems
• Testing linear.hypotheses in generalized multivariate linear models

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