PMID: 9533261Apr 9, 1998Paper

Approximate hierarchical modelling of discrete data in epidemiology

Statistical Methods in Medical Research
N BreslowRobert Platt

Abstract

Hierarchical models are used in epidemiology to estimate and analyse multiple, related relative risks. Examples include meta-analyses of series of 2 x 2 tables and mapping of spatially correlated disease rates. Empirical transform and penalized quasilikelihood procedures, both of which may be implemented using standard programs for mixed model analysis, provide satisfactory approximate inferences for these problems when cell frequencies are large. Simulation studies show that, in certain situations involving small cell frequencies, penalized quasilikelihood provides satisfactory estimates of variance components and regression coefficients whereas the empirical transform approach does not.

References

Sep 1, 1986·Controlled Clinical Trials·R DerSimonian, N Laird
Dec 1, 1985·American Journal of Epidemiology·D C ThomasB G Armstrong
Feb 28, 1995·Statistics in Medicine·C S BerkeyG A Colditz

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Citations

Feb 6, 2020·Biometrical Journal. Biometrische Zeitschrift·Stefano PelusoAngelo Auricchio
Apr 10, 2020·International Journal of Environmental Health Research·Sabrina LiSusan J Elliott
Apr 16, 1999·Statistics in Medicine·R W PlattN Breslow
Aug 28, 2016·Statistical Methods in Medical Research·Andrea RieblerHåvard Rue
Dec 21, 2000·Statistics in Medicine·R M TurnerS G Thompson
Mar 6, 2018·Research Synthesis Methods·Ralf BenderGuido Skipka

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