Things that make us different: analysis of deviance with time-use data

The constrained, non-normal nature of time-use data poses a challenge to ordinary analysis of variance. This paper investigates a computationally simple variance decomposition technique suitable for those data. As a by-product of the analysis, a measure of fit for systems of time-demand equations is proposed that possesses several useful properties.     

A spatial randomness test based on the box-counting dimension

AStA Advances in Statistical Analysis - Statistical modelling of a spatial point pattern often begins by testing the hypothesis of spatial randomness. Classical tests are based on quadrat counts...     

Effects of air pollution and weather on the initial COVID-19 outbreaks in United States,Italy, Spain,and China: A comparative study

Contrasting effects have been identified in association of weather (temperature and humidity) and pollutant gases with COVID-19 infection, which could be derived from the influence of lockdowns and season change. The influence of pollutant gases and climate during the initial phases of the pandemic, before the closures and the change of season in the northern hemisphere, is unknown. Here, we used a spatial-temporal Bayesian zero-inflated-Poisson model to test for short-term associations of weather and pollutant gases with the relative risk of COVID-19 disease in China (first outbreak) and the countries with more cases during the initial pandemic (the United States, Spain and Italy), considering also the effects of season and lockdown. We found contrasting association between pollutant gases and COVID-19 risk in the United States, Italy, and Spain, while in China it was negatively associated (except for SO₂). COVID-19 risk was positively associated with specific humidity in all countries, while temperature presented a negative effect. Our findings showed that short-term associations of air pollutants with COVID-19 infection vary strongly between countries, while generalized effects of temperature (negative) and humidity (positive) with COVID-19 was found. Our results show novel information about the influence of pollution and weather on the initial outbreaks, which contribute to unravel the mechanisms during the beginning of the pandemic.     

Modeling immunogenecity data to establish screening bioassays cut point

The response of immunogenecity anti-drug antibody (ADA) generally includes biological and analytical variability. The nature of biological and analytical variations may lead to a variety of symmetric and asymmetric ADA data. As a result, current statistical methods may yield unreliable results because these methods assume special types of symmetric or asymmetric ADA data. In this paper, we survey and compare parametric models that are useful for analyzing a variety of asymmetric data that have rarely been used to calculate assay cut points. These models include symmetric distributions as limiting case; therefore, they are useful in the analysis of a variety of symmetric data. We also investigate two nonparametric approaches that have received little attention in screening cut point calculations. A simulation study was conducted to compare the performance of the methods. We evaluate the methods using four published different types of data, and make recommendations concerning the use of the methods.     

The effect of artificial light on bat richness and nocturnal soundscapes along an urbanization gradient in an arid landscape of central Peru

Urbanization usually reduces bat richness; however, the presence of green areas within cities and peripheral rural areas in arid ecosystems may provide microhabitats for some species. Light pollution is a major feature of urbanization, but its impact on bat behavior appears to be species-specific and previous studies have documented contrasting responses. Moreover, the effect of urbanization on bat species has been poorly studied in arid regions. We assessed the effect of artificial night light intensity (as a proxy of urbanization) on both bat occupancy and the acoustic space used (ASU) in an urbanization gradient in Peruvian central coast, based on passive acoustic recorders. We collected 26,169 recordings from 19 sites which resulted in 579 independent detections of 15 bat species. Variation in both ASU and species richness was best explained by artificial night light intensity. Species-specific effects of the artificial night light intensity based on a multi-species occupancy modeling showed that this covariate had a negative effect on occupancy for most of the bat species (12 species). ASU and both observed and posterior bat species richness were positively correlated, suggesting that ASU can be used as a proxy of bat richness. This study provides evidence that both bat richness and occupancy decrease with artificial light intensity; nevertheless, eight species used urban areas, similar to results found in other cities around the world.