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

Genetic distance predicts trait differentiation at the subpopulation but not the individual level in eelgrass, Zostera marina.

Ecological studies often assume that genetically similar individuals will be more similar in phenotypic traits, such that genetic diversity can serve as a proxy for trait diversity. Here, we explicitly test the relationship between genetic relatedness and trait distance using 40 eelgrass (Zostera marina) genotypes from five sites within Bodega Harbor, CA. We measured traits related to nutrient uptake, morphology, biomass and growth, photosynthesis, and chemical deterrents for all genotypes. We used these trait measurements to calculate a multivariate pairwise trait distance for all possible genotype combinations. We then estimated pairwise relatedness from 11 microsatellite markers. We found significant trait variation among genotypes for nearly every measured trait; however, there was no evidence of a significant correlation between pairwise genetic relatedness and multivariate trait distance among individuals. However, at the subpopulation level (sites within a harbor), genetic (FST) and trait differentiation were positively correlated. Our work suggests that pairwise relatedness estimated from neutral marker loci is a poor proxy for trait differentiation between individual genotypes. It remains to be seen whether genomewide measures of genetic differentiation or easily measured "master" traits (like body size) might provide good predictions of overall trait differentiation

Polling bias and undecided voter allocations: US Presidential elections, 2004 - 2016

Accounting for undecided and uncertain voters is a challenging issue for predicting election results from public opinion polls. Undecided voters typify the uncertainty of swing voters in polls but are often ignored or allocated to each candidate in a simple, deterministic manner. Historically this may have been adequate because the undecided were comparatively small enough to assume that they do not affect the relative proportions of the decided voters. However, in the presence of high numbers of undecided voters, these static rules may in fact bias election predictions from election poll authors and meta-poll analysts. In this paper, we examine the effect of undecided voters in the 2016 US presidential election to the previous three presidential elections. We show there were a relatively high number of undecided voters over the campaign and on election day, and that the allocation of undecided voters in this election was not consistent with two-party proportional (or even) allocations. We find evidence that static allocation regimes are inadequate for election prediction models and that probabilistic allocations may be superior. We also estimate the bias attributable to polling agencies, often referred to as "house effects".Comment: 32 pages, 9 figures, 6 table

Graphics for uncertainty

Graphical methods such as colour shading and animation, which are widely available, can be very effective in communicating uncertainty. In particular, the idea of a ‘density strip’ provides a conceptually simple representation of a distribution and this is explored in a variety of settings, including a comparison of means, regression and models for contingency tables. Animation is also a very useful device for exploring uncertainty and this is explored particularly in the context of flexible models, expressed in curves and surfaces whose structure is of particular interest. Animation can further provide a helpful mechanism for exploring data in several dimensions. This is explored in the simple but very important setting of spatiotemporal data

Kinematic discrimination of ataxia in horses is facilitated by blindfolding

BACKGROUND: Agreement among experienced clinicians is poor when assessing the presence and severity of ataxia, especially when signs are mild. Consequently, objective gait measurements might be beneficial for assessment of horses with neurological diseases. OBJECTIVES: To assess diagnostic criteria using motion capture to measure variability in spatial gait-characteristics and swing duration derived from ataxic and non-ataxic horses, and to assess if variability increases with blindfolding. STUDY DESIGN: Cross-sectional. METHODS: A total of 21 horses underwent measurements in a gait laboratory and live neurological grading by multiple raters. In the gait laboratory, the horses were made to walk across a runway surrounded by a 12-camera motion capture system with a sample frequency of 240 Hz. They were made to walk normally and with a blindfold in at least three trials each. Displacements of reflective markers on head, fetlock, hoof, fourth lumbar vertebra, tuber coxae and sacrum derived from three to four consecutive strides were processed and descriptive statistics, receiver operator characteristics (ROC) to determine the diagnostic sensitivity, specificity and area under the curve (AUC), and correlation between median ataxia grade and gait parameters were determined. RESULTS: For horses with a median ataxia grade ≥2, coefficient of variation for the location of maximum vertical displacement of pelvic and thoracic distal limbs generated good diagnostic yield. The hoofs of the thoracic limbs yielded an AUC of 0.81 with 64% sensitivity and 90% specificity. Blindfolding exacerbated the variation for ataxic horses compared to non-ataxic horses with the hoof marker having an AUC of 0.89 with 82% sensitivity and 90% specificity. MAIN LIMITATIONS: The low number of consecutive strides per horse obtained with motion capture could decrease diagnostic utility. CONCLUSIONS: Motion capture can objectively aid the assessment of horses with ataxia. Furthermore, blindfolding increases variation in distal pelvic limb kinematics making it a useful clinical tool

Optimizing passive acoustic sampling of bats in forests

Passive acoustic methods are increasingly used in biodiversity research and monitoring programs because they are cost-effective and permit the collection of large datasets. However, the accuracy of the results depends on the bioacoustic characteristics of the focal taxa and their habitat use. In particular, this applies to bats which exhibit distinct activity patterns in three-dimensionally structured habitats such as forests. We assessed the performance of 21 acoustic sampling schemes with three temporal sampling patterns and seven sampling designs. Acoustic sampling was performed in 32 forest plots, each containing three microhabitats: forest ground, canopy, and forest gap. We compared bat activity, species richness, and sampling effort using species accumulation curves fitted with the clench equation. In addition, we estimated the sampling costs to undertake the best sampling schemes. We recorded a total of 145,433 echolocation call sequences of 16 bat species. Our results indicated that to generate the best outcome, it was necessary to sample all three microhabitats of a given forest location simultaneously throughout the entire night. Sampling only the forest gaps and the forest ground simultaneously was the second best choice and proved to be a viable alternative when the number of available detectors is limited. When assessing bat species richness at the 1-km(2) scale, the implementation of these sampling schemes at three to four forest locations yielded highest labor cost-benefit ratios but increasing equipment costs. Our study illustrates that multiple passive acoustic sampling schemes require testing based on the target taxa and habitat complexity and should be performed with reference to cost-benefit ratios. Choosing a standardized and replicated sampling scheme is particularly important to optimize the level of precision in inventories, especially when rare or elusive species are expected

Winter Conditions Influence Biological Responses of Migrating Hummingbirds

Conserving biological diversity given ongoing environmental changes requires the knowledge of how organisms respond biologically to these changes; however, we rarely have this information. This data deficiency can be addressed with coordinated monitoring programs that provide field data across temporal and spatial scales and with process-based models, which provide a method for predicting how species, in particular migrating species that face different conditions across their range, will respond to climate change. We evaluate whether environmental conditions in the wintering grounds of broad-tailed hummingbirds influence physiological and behavioral attributes of their migration. To quantify winter ground conditions, we used operative temperature as a proxy for physiological constraint, and precipitation and the normalized difference vegetation index (NDVI) as surrogates of resource availability. We measured four biological response variables: molt stage, timing of arrival at stopover sites, body mass, and fat. Consistent with our predictions, we found that birds migrating north were in earlier stages of molt and arrived at stopover sites later when NDVI was low. These results indicate that wintering conditions impact the timing and condition of birds as they migrate north. In addition, our results suggest that biologically informed environmental surrogates provide a valuable tool for predicting how climate variability across years influences the animal populations

Charting self-esteem during marital dissolution.

ObjectiveThe purpose of this study was to chart changes in self-esteem before and after marital dissolution to identify the factors that shape individuals' self-esteem during this life transition.MethodWe analyzed 10 annual waves of self-esteem data from 291 divorcees from a nationally representative panel study of the Netherlands (N ~ 13,000). We charted the course of self-esteem before and after marital dissolution and tested a broad set of moderator variables that may shape individuals' self-esteem trajectories.ResultsThe average divorcee experienced significant decrease in self-esteem preceding marital dissolution and remained stable afterward. There were substantial individual differences in self-esteem trajectories, both before and after marital separation. Divorcees who experienced financial hardship, were affiliated with a church or religion, or scored low in Conscientiousness showed the most pronounced decrease in self-esteem during the years approaching marital dissolution.ConclusionThis study highlights the importance of assessing people multiple times before and after marital dissolution to dissect how people approach and respond to this life event. Results are consistent with perspectives that view divorce as an opportunity to abate the strains of an unhappy marriage

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

Not all surveillance data are created equal—A multi‐method dynamic occupancy approach to determine rabies elimination from wildlife

1. A necessary component of elimination programmes for wildlife disease is effective surveillance. The ability to distinguish between disease freedom and non‐detection can mean the difference between a successful elimination campaign and new epizootics. Understanding the contribution of different surveillance methods helps to optimize and better allocate effort and develop more effective surveillance programmes. 2. We evaluated the probability of rabies virus elimination (disease freedom) in an enzootic area with active management using dynamic occupancy modelling of 10 years of raccoon rabies virus (RABV) surveillance data (2006–2015) collected from three states in the eastern United States. We estimated detection probability of RABV cases for each surveillance method (e.g. strange acting reports, roadkill, surveillance‐trapped animals, nuisance animals and public health samples) used by the USDA National Rabies Management Program. 3. Strange acting, found dead and public health animals were the most likely to detect RABV when it was present, and generally detectability was higher in fall– winter compared to spring–summer. Found dead animals in fall–winter had the highest detection at 0.33 (95% CI: 0.20, 0.48). Nuisance animals had the lowest detection probabilities (~0.02). 4. Areas with oral rabies vaccination (ORV) management had reduced occurrence probability compared to enzootic areas without ORV management. RABV occurrence was positively associated with deciduous and mixed forests and medium to high developed areas, which are also areas with higher raccoon (Procyon lotor) densities. By combining occupancy and detection estimates we can create a probability of elimination surface that can be updated seasonally to provide guidance on areas managed for wildlife disease. 5. Synthesis and applications. Wildlife disease surveillance is often comprised of a combination of targeted and convenience‐based methods. Using a multi‐method analytical approach allows us to compare the relative strengths of these methods, providing guidance on resource allocation for surveillance actions. Applying this multi‐method approach in conjunction with dynamic occupancy analyses better informs management decisions by understanding ecological drivers of disease occurrence