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Public health research often concerns relationships between exposures and correlated count outcomes. When counts exhibit more 0s than expected under Poisson sampling, the zero‐inflated Poisson (ZIP) model with random effects may be used. However, the latent class formulation of the ZIP model can make marginal inference on the population sampled challenging. The paper presents a marginalized ZIP model...
Strategic abstentions—in which legislators abstain from votes for ideological reasons—are a poorly understood feature of legislative voting records. The paper discusses a spatial model for legislators’ revealed preferences that accounts for abstentions when missing values are non‐ignorable and allows us to measure the pervasiveness of strategic abstention by identifying legislators who consistently...
Often in regionally aggregated spatiotemporal models, a single variance parameter is used to capture variability in the spatial structure of the model, ignoring the effect that spatially varying factors may have on the variability in the underlying process. We extend existing methodologies to allow for region‐specific variance components in our analysis of monthly asthma hospitalization rates in California...
The Penn Ovarian Aging Study tracked a population‐based sample of 436 women aged 35–47 years to determine associations between reproductive hormone levels and menopausal symptoms. We develop a joint modelling method that uses the individual level longitudinal measurements of follicle stimulating hormone (FSH) to predict the risk of severe hot flashes in a manner that distinguishes long‐term trends...
Previous climate research concluded that causal influences which have contributed to changes in frost risk in south‐eastern Australia include greenhouse gas concentration, El‐Niño southern oscillation and other effects. Some of the climatic indices representing these effects have spatiotemporal misalignment and may have a spatially and temporally varying effect on observed data. Other indices are...
Predicting the occurrence and timing of adverse pregnancy events such as preterm birth is an important analytical challenge in obstetrical practice. Developing statistical approaches that can be used to assess the risk and timing of these adverse events will provide clinicians with tools for individualized risk assessment that account for a woman's prior pregnancy history. Often adverse pregnancy...
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