When Should Epidemiologic Regressions Use Random Coefficients?

DOI10.1111/j.0006-341X.2000.00915.xzbMath1060.62618OpenAlexW2106716774WikidataQ44736856 ScholiaQ44736856MaRDI QIDQ4670441

Sander Greenland

Publication date: 22 April 2005

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.0006-341x.2000.00915.x

zbMATH Keywords

Bayesian statisticsvariance componentsrelative riskshrinkagemixed modelsrisk assessmentcausal inferencemultilevel modelempirical Bayes estimatorsepidemiologic methodshierarchical regressionrandom-coefficient regression

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Analysis of variance and covariance (ANOVA) (62J10) Empirical decision procedures; empirical Bayes procedures (62C12)

Related Items (9)

Relaxation penalties and priors for plausible modeling of nonidentified bias sources ⋮ Comment: The need for syncretism in applied statistics ⋮ A nondegenerate penalized likelihood estimator for variance parameters in multilevel models ⋮ Tests for qualitative features in the random coefficients model ⋮ Putting Background Information About Relative Risks into Conjugate Prior Distributions ⋮ Generalized Conjugate Priors for Bayesian Analysis of Risk and Survival Regressions ⋮ Subject-specific odds ratios in binomial GLMMs with continuous response ⋮ Discussion of: ``Akaike Memorial Lecture 2020: Some of the challenges of statistical applications ⋮ The Performance of Random Coefficient Regression in Accounting for Residual Confounding

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