Landscape Context Influences the Abundance and Richness of Native Lady Beetles Occupying Urban Vacant Land

Urban Ecosystems - Urban insect communities are structured by hierarchical filters including regional processes, human facilitation, and species interactions. We sought to inform future urban...     

Likelihood-free approximate Gibbs sampling

Likelihood-free methods such as approximate Bayesian computation (ABC) have extended the reach of statistical inference to problems with computationally intractable likelihoods. Such approaches perform well for small-to-moderate dimensional problems, but suffer a curse of dimensionality in the number of model parameters. We introduce a likelihood-free approximate Gibbs sampler that naturally circumvents the dimensionality issue by focusing on lower-dimensional conditional distributions. These distributions are estimated by flexible regression models either before the sampler is run, or adaptively during sampler implementation. As a result, and in comparison to Metropolis-Hastings-based approaches, we are able to fit substantially more challenging statistical models than would otherwise be possible. We demonstrate the sampler’s performance via two simulated examples, and a real analysis of Airbnb rental prices using a intractable high-dimensional multivariate nonlinear state-space model with a 36-dimensional latent state observed on 365 time points, which presents a real challenge to standard ABC techniques.     

Multiple event times in the presence of informative censoring: modeling and analysis by copulas

Motivated by a breast cancer research program, this paper is concerned with the joint survivor function of multiple event times when their observations are subject to informative censoring caused by a terminating event. We formulate the correlation of the multiple event times together with the time to the terminating event by an Archimedean copula to account for the informative censoring. Adapting the widely used two-stage procedure under a copula model, we propose an easy-to-implement pseudo-likelihood based procedure for estimating the model parameters. The approach yields a new estimator for the marginal distribution of a single event time with semicompeting-risks data. We conduct both asymptotics and simulation studies to examine the proposed approach in consistency, efficiency, and robustness. Data from the breast cancer program are employed to illustrate this research.

     

Reactive and proactive aggression in children with and without ADHD and negative emotional lability

Children with attention‐deficit/hyperactivity disorder (ADHD) exhibit marked difficulty with frequent and intense shifts in negative or positive emotions, referred to as emotional lability. This study examines the relationships between negative emotional lability (NEL), ADHD, and reactive and proactive aggression. A community sample of 96 children (53 with ADHD, 43 control) ages 8–12 and their parents completed a baseline session include a diagnostic structured interview and the Reactive–Proactive Aggression Questionnaire (RPAQ). Parents then rated their child's NEL using the Positive and Negative Affect Scale as part of an Ecological Momentary Assessment protocol 3 times a day for 28 days. Seventy‐three participants (37 with ADHD, 36 control) completed the RPAQ at follow‐up. Hierarchical regression analyses indicated that NEL significantly and independently estimates reactive aggression at baseline and follow‐up, regardless of ADHD status. NEL and ADHD status significantly estimates concurrent proactive aggression, but not at follow‐up. Results of this study suggest that NEL accounts for a significant amount of the variability in reactive aggression, a common difficulty in children with ADHD. Further, individuals that are reportedly emotionally labile become more reactively aggressive over time. Both ADHD diagnostic and NEL are predictors of proactive aggression at baseline, although no interaction occurred.     

Young children's perceptions and beliefs about hypothetical shy,unsociable, and socially avoidant peers at school

The aim of this study was to explore young children's perceptions, beliefs, and anticipated outcomes about different types of social withdrawal (shyness, unsociability, social avoidance). Participants were N = 212 children (n = 110 boys) aged 2.55–6.37 years (M = 4.86, SD = 0.89) recruited from three preschools and kindergartens in Italy. Children were interviewed individually and asked about hypothetical peers displaying different types of social withdrawal (i.e., shy, unsociable, socially avoidant) and for comparison purposes, aggressive and socially competent behaviors were also assessed. Among the three vignettes depicting types of withdrawn children, children rated the hypothetical shy peer as having the highest social motivations, the unsociable peer as receiving the least sympathy from others, and the avoidant peer as being the least intelligent and least liked by the teacher. In addition, girls reported wanting to play more with the shy peer than boys, and kindergarteners reported a higher affiliative preference for all subtypes of socially withdrawn peers than preschoolers. These findings suggest that Italian young children have a quite sophisticated ability to differentiate among the different social motivations and emotions that may underlie social withdrawal.