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Biostatistics Volume 21 Issue 3

Subject Areas: Statistics, Probability and Uncertainty
Publisher: Oxford University Press - Oxford University Press
ISSN: 1465-4644
SJR: 84

Open Access

Journal Article

A Bayesian mixture modeling approach for public health surveillance

Boulieri, Areti; Bennett, James E; Blangiardo, Marta

2020 Biostatistics

doi:10.1093/biostatistics/kxy038 pmid:30252021

Summary Spatial monitoring of trends in health data plays an important part of public health surveillance. Most commonly, it is used to understand the etiology of a public health issue, to assess the impact of an intervention, or to provide detection of unusual behavior. In this article, we...
Open Access

Journal Article

Model selection and parameter estimation for dynamic epidemic models via iterated filtering: application to rotavirus in Germany

Stocks, Theresa; Britton, Tom; Höhle, Michael

2020 Biostatistics

doi:10.1093/biostatistics/kxy057 pmid:30265310

Summary Despite the wide application of dynamic models in infectious disease epidemiology, the particular modeling of variability in the different model components is often subjective rather than the result of a thorough model selection process. This is in part because inference for a stochastic...
Open Access

Journal Article

Non-parametric frailty Cox models for hierarchical time-to-event data

Gasperoni, Francesca; Ieva, Francesca; Paganoni, Anna Maria; Jackson, Christopher H; Sharples, Linda

2020 Biostatistics

doi:10.1093/biostatistics/kxy071 pmid:30590499

Summary We propose a novel model for hierarchical time-to-event data, for example, healthcare data in which patients are grouped by their healthcare provider. The most common model for this kind of data is the Cox proportional hazard model, with frailties that are common to patients in the same...
Open Access

Journal Article

MACPET: model-based analysis for ChIA-PET

Vardaxis, Ioannis; Drabløs, Finn; Rye, Morten B; Lindqvist, Bo Henry

2020 Biostatistics

doi:10.1093/biostatistics/kxy084 pmid:30698663

Summary We present model-based analysis for ChIA-PET (MACPET), which analyzes paired-end read sequences provided by ChIA-PET for finding binding sites of a protein of interest. MACPET uses information from both tags of each PET and searches for binding sites in a two-dimensional space, while...

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