Estimating Herd-Specific Force of Infection by Using Random-Effects Models for Clustered Binary Data and Monotone Fractional Polynomials

DOI10.1111/j.1467-9876.2006.00555.xzbMath1109.62098OpenAlexW2134685231WikidataQ56880833 ScholiaQ56880833MaRDI QIDQ3435364

Niel Hens, Ziv Shkedy, Helena Geys, Frank Boelaert, Marc Aerts, Christel Faes, Hans Laevens, Koen Mintiens

Publication date: 26 April 2007

Published in: Journal of the Royal Statistical Society Series C: Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9876.2006.00555.x

zbMATH Keywords

clusteringfractional polynomialsforce of infectionrandom-effects approach

Mathematics Subject Classification ID

Epidemiology (92D30) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (1)

Handling missingness when modeling the force of infection from clustered seroprevalence data

Uses Software

• PROC NLMIXED

Cites Work

• Unnamed Item
• Marginal Analyses of Clustered Data When Cluster Size Is Informative
• Random-Effects Models for Longitudinal Data
• Estimation from current-status data in continuous time
• Models for discrete longitudinal data.
• Within-cluster resampling
• Use of fractional polynomials for dose-response modelling and quantitative risk assessment in developmental toxicity studies
• Estimation of the Basic Reproduction Number for Infectious Diseases from Age-Stratified Serological Survey Data
• A new look at the statistical model identification

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