Multivariate Hierarchical Frameworks for Modelling Delayed Reporting in Count Data

In many fields and applications count data can be subject to delayed reporting. This is where the total count, such as the number of disease cases contracted in a given week, may not be immediately available, instead arriving in parts over time. For short term decision making, the statistical challenge lies in predicting the total count based on any observed partial counts, along with a robust quantification of uncertainty. In this article we discuss previous approaches to modelling delayed reporting and present a multivariate hierarchical framework where the count generating process and delay mechanism are modelled simultaneously. Unlike other approaches, the framework can also be easily adapted to allow for the presence of under-reporting in the final observed count. To compare our approach with existing frameworks, one of which we extend to potentially improve predictive performance, we present a case study of reported dengue fever cases in Rio de Janeiro. Based on both within-sample and out-of-sample posterior predictive model checking and arguments of interpretability, adaptability, and computational efficiency, we discuss the advantages and disadvantages of each modelling framework.Comment: Biometrics (2019

Assessment of available anatomical characters for linking living mammals to fossil taxa in phylogenetic analyses

ORCID: 0000-0003-4919-8655© 2016 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. The file attached is the published version of the article

Additive quantile regression for clustered data with an application to children's physical activity

Additive models are flexible regression tools that handle linear as well as nonlinear terms. The latter are typically modelled via smoothing splines. Additive mixed models extend additive models to include random terms when the data are sampled according to cluster designs (e.g., longitudinal). These models find applications in the study of phenomena like growth, certain disease mechanisms and energy consumption in humans, when repeated measurements are available. In this paper, we propose a novel additive mixed model for quantile regression. Our methods are motivated by an application to physical activity based on a dataset with more than half million accelerometer measurements in children of the UK Millennium Cohort Study. In a simulation study, we assess the proposed methods against existing alternatives.Comment: 50 pages, 4 figures, 2 tables (18 supplementary tables

Habitual accountability routines in the boardroom: How boards balance control and collaboration

open3siCorporate accountability is a complex chain of reporting that reaches from external stakeholders into the organization’s management structure. The transition from external to internal accountability mechanisms primarily occurs at the board of directors. Yet outside of incentive mechanisms, we know surprisingly little about how internal actors (management) are held to account by the representatives of external shareholders (the board). This paper explores the process of accountability at this transition point by documenting the routines used by boards to hold the firm’s management to account. In so doing we develop our understanding of the important transition between internal and external firm accountability.embargoed_20190401Nicholson, Gavin; Pugliese, Amedeo; Bezemer, Pieter JanNicholson, Gavin; Pugliese, Amedeo; Bezemer, Pieter Ja

Incorporating weather information into real-time speed estimates: comparison of alternative models

Weather information is frequently requested by travelers. Prior literature indicates that inclement weather is one of the most important factors contributing to traffic congestion and crashes. In this paper, we propose a methodology to use real-time weather information to predict future speeds. The reason for doing so is to ultimately have the capability to disseminate weather-responsive travel time estimates to those requesting information. Using a stratified sampling technique, we select cases with different weather conditions (precipitation levels) and use a linear regression model (called the base model) and a statistical learning model (using Support Vector Machines for Regression) to predict 30-minute ahead speeds. One of the major inputs into a weather-responsive short-term speed prediction method is weather forecasts; however, weather forecasts may themselves be inaccurate. We assess the effects of such inaccuracies by means of simulations. The predictive accuracy of the SVR models show that statistical learning methods may be useful in bringing together streaming forecasted weather data and real-time information on downstream traffic conditions to enable travelers to make informed choices

Multiple morbidities in companion dogs: a novel model for investigating age-related disease

The proportion of men and women surviving over 65 years has been steadily increasing over the last century. In their later years, many of these individuals are afflicted with multiple chronic conditions, placing increasing pressure on healthcare systems. The accumulation of multiple health problems with advanced age is well documented, yet the causes are poorly understood. Animal models have long been employed in attempts to elucidate these complex mechanisms with limited success. Recently, the domestic dog has been proposed as a promising model of human aging for several reasons. Mean lifespan shows twofold variation across dog breeds. In addition, dogs closely share the environments of their owners, and substantial veterinary resources are dedicated to comprehensive diagnosis of conditions in dogs. However, while dogs are therefore useful for studying multimorbidity, little is known about how aging influences the accumulation of multiple concurrent disease conditions across dog breeds. The current study examines how age, body weight, and breed contribute to variation in multimorbidity in over 2,000 companion dogs visiting private veterinary clinics in England. In common with humans, we find that the number of diagnoses increases significantly with age in dogs. However, we find no significant weight or breed effects on morbidity number. This surprising result reveals that while breeds may vary in their average longevity and causes of death, their age-related trajectories of morbidities differ little, suggesting that age of onset of disease may be the source of variation in lifespan across breeds. Future studies with increased sample sizes and longitudinal monitoring may help us discern more breed-specific patterns in morbidity. Overall, the large increase in multimorbidity seen with age in dogs mirrors that seen in humans and lends even more credence to the value of companion dogs as models for human morbidity and mortality

Bacterial microbiota composition of a common ectoparasite of cavity‐breeding birds, the Hen Flea Ceratophyllus gallinae

Experimental field studies have demonstrated negative fitness consequences of Hen Flea Ceratophyllus gallinae infestations for bird hosts, yet it is currently unclear whether these negative effects are a direct consequence of flea-induced blood loss or a result of flea-borne pathogen transmission. Here we used a 16S rRNA gene sequencing approach to characterize the bacterial microbiota community of Hen Fleas collected from Great Tit Parus major nests and found that Brevibacterium (Actinobacteria), Staphylococcus (Firmicutes), Stenotrophomonas (Proteobacteria), Massilia (Proteobacteria), as well as the arthropod endosymbionts 'Candidatus Lariskella' and 'Candidatus Midichloria' were most abundant. We found evidence for the occurrence of Staphylococcus spp. in Hen Fleas, which may cause opportunistic infections in bird hosts, but not of other known pathogens commonly transmitted by other flea species, such as Bartonella spp. or Rickettsia spp. However, Hen Fleas might transmit other pathogens (e.g. viruses or bacteria that are not currently recognized as bird pathogens), which may contribute to the negative fitness consequences of Hen Flea infestations in addition to direct blood loss or secondary infections of wounds caused by biting fleas.Peer reviewe

Detecting similarities among distant homologous proteins by comparison of domain flexibilities

Aim of this work is to assess the informativeness of protein dynamics in the detection of similarities among distant homologous proteins. To this end, an approach to perform large-scale comparisons of protein domain flexibilities is proposed. CONCOORD is confirmed as a reliable method for fast conformational sampling. The root mean square fluctuation of alpha carbon positions in the essential dynamics subspace is employed as a measure of local flexibility and a synthetic index of similarity is presented. The dynamics of a large collection of protein domains from ASTRAL/SCOP40 is analyzed and the possibility to identify relationships, at both the family and the superfamily levels, on the basis of the dynamical features is discussed. The obtained picture is in agreement with the SCOP classification, and furthermore suggests the presence of a distinguishable familiar trend in the flexibility profiles. The results support the complementarity of the dynamical and the structural information, suggesting that information from dynamics analysis can arise from functional similarities, often partially hidden by a static comparison. On the basis of this first test, flexibility annotation can be expected to help in automatically detecting functional similarities otherwise unrecoverable. © 2007 The Author(s)

Intraspecific variation in thermal acclimation and tolerance between populations of the winter ant, Prenolepis imparis.

Thermal phenotypic plasticity, otherwise known as acclimation, plays an essential role in how organisms respond to short-term temperature changes. Plasticity buffers the impact of harmful temperature changes; therefore, understanding variation in plasticity in natural populations is crucial for understanding how species will respond to the changing climate. However, very few studies have examined patterns of phenotypic plasticity among populations, especially among ant populations. Considering that this intraspecies variation can provide insight into adaptive variation in populations, the goal of this study was to quantify the short-term acclimation ability and thermal tolerance of several populations of the winter ant, Prenolepis imparis. We tested for correlations between thermal plasticity and thermal tolerance, elevation, and body size. We characterized the thermal environment both above and below ground for several populations distributed across different elevations within California, USA. In addition, we measured the short-term acclimation ability and thermal tolerance of those populations. To measure thermal tolerance, we used chill-coma recovery time (CCRT) and knockdown time as indicators of cold and heat tolerance, respectively. Short-term phenotypic plasticity was assessed by calculating acclimation capacity using CCRT and knockdown time after exposure to both high and low temperatures. We found that several populations displayed different chill-coma recovery times and a few displayed different heat knockdown times, and that the acclimation capacities of cold and heat tolerance differed among most populations. The high-elevation populations displayed increased tolerance to the cold (faster CCRT) and greater plasticity. For high-temperature tolerance, we found heat tolerance was not associated with altitude; instead, greater tolerance to the heat was correlated with increased plasticity at higher temperatures. These current findings provide insight into thermal adaptation and factors that contribute to phenotypic diversity by revealing physiological variance among populations