Choice of units of analysis and modeling strategies in multilevel hierarchical models

DOI10.1016/J.CSDA.2003.12.003zbMath1429.62482OpenAlexW1992510186WikidataQ59901709 ScholiaQ59901709MaRDI QIDQ957034

Tomasz Burzykowski, Geert Molenberghs, Ariel Alonso Abad, Didier Renard, José Cortiñas Abrahantes, Ziv Shkedy

Publication date: 26 November 2008

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/1942/675

zbMATH Keywords

random effectslinear mixed modelsurrogate endpointmeta-analytic approach

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (9)

Center-within-trial versus trial-level evaluation of surrogate endpoints ⋮ On the relationship between the causal‐inference and meta‐analytic paradigms for the validation of surrogate endpoints ⋮ Simplified modeling strategies for surrogate validation with multivariate failure-time data ⋮ Estimating negative variance components from Gaussian and non-Gaussian data: a mixed models approach ⋮ The meta-analytic framework for the evaluation of surrogate endpoints in clinical trials ⋮ Surrogate Marker Evaluation from an Information Theory Perspective ⋮ Statistical evaluation of surrogate endpoints with examples from cancer clinical trials ⋮ Unbalanced cluster sizes and rates of convergence in mixed-effects models for clustered data ⋮ Flexible surrogate marker evaluation from several randomized clinical trials with continuous endpoints, using R and SAS

Cites Work

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• Influence diagnostics for generalized linear mixed models: applications to clustered data.
• Simplified hierarchical linear models for the evaluation of surrogate endpoints
• The validation of surrogate endpoints in meta-analyses of randomized experiments
• Linear mixed models for longitudinal data

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