Clustered data with small sample sizes: Comparing the performance of model-based and design-based approaches

DOI10.1080/03610918.2014.983648zbMath1359.62257OpenAlexW2085920193MaRDI QIDQ2974894

Jeffery R. Harring, Daniel McNeish

Publication date: 11 April 2017

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

Full work available at URL: https://doi.org/10.1080/03610918.2014.983648

zbMATH Keywords

GEEmixed modelmultilevel modelsmall sample sizeKenward-Roger

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Linear regression; mixed models (62J05) Generalized linear models (logistic models) (62J12)

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Can \(p\)-values be meaningfully interpreted without random sampling? ⋮ ANOVA with binary variables: the F-test and some alternatives ⋮ A reliable small sample classification algorithm by Elman neural network based on PLS and GA

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