Search results for "Hierarchical"

Data from: Wood-inhabiting fungi with tight associations with other species have declined as a response to forest management

2016

Research on mutualistic and antagonistic networks, such as plant–pollinator and host–parasite networks, has shown that species interactions can influence and be influenced by the responses of species to environmental perturbations. Here we examine whether results obtained for directly observable networks generalize to more complex networks in which species interactions cannot be observed directly. As a case study, we consider data on the occurrences of 98 wood-inhabiting fungal species in managed and natural forests. We specifically ask if and how much the positions of wood-inhabiting fungal species within the interaction networks influence their responses to forest management. For this, we…

Un ecosistema malalt: la lluita contra la resistència a antibiòtics des d’una perspectiva global

2013

La produccio antropogenica d'antibiotics ha provocat una malaltia dels ecosistemes microbians de dimensio planetaria, la repercussio mes immediata de la qual per a l'home es la intractabilitat de les infeccions. La comprensio del fenomen i les possibilitats d'intervencio requereixen nous metodes conceptuals, analitics i tecnologics.

Epidemiological Information Systems

2008

Weighted Integration of Duration Information Across Visual and Auditory Modality Is Influenced by Modality-Specific Attention.

2021

We constantly integrate multiple types of information from different sensory modalities. Generally, such integration is influenced by the modality that we attend to. However, for duration perception, it has been shown that when duration information from visual and auditory modalities is integrated, the perceived duration of the visual stimulus leaned toward the duration of the auditory stimulus, irrespective of which modality was attended. In these studies, auditory dominance was assessed using visual and auditory stimuli with different durations whose timing of onset and offset would affect perception. In the present study, we aimed to investigate the effect of attention on duration integr…

Multilevel Latent Profile Analysis With Covariates : Identifying Job Characteristics Profiles in Hierarchical Data as an Example

2018

Latent profile analysis (LPA) is a person-centered method commonly used in organizational research to identify homogeneous subpopulations of employees within a heterogeneous population. However, in the case of nested data structures, such as employees nested in work departments, multilevel techniques are needed. Multilevel LPA (MLPA) enables adequate modeling of subpopulations in hierarchical data sets. MLPA enables investigation of variability in the proportions of Level 1 profiles across Level 2 units, and of Level 2 latent classes based on the proportions of Level 1 latent profiles and Level 1 ratings, and the extent to which covariates drawn from the different hierarchical levels of th…

Conditional predictive inference for online surveillance of spatial disease incidence

2011

This paper deals with the development of statistical methodology for timely detection of incident disease clusters in space and time. The increasing availability of data on both the time and the location of events enables the construction of multivariate surveillance techniques, which may enhance the ability to detect localized clusters of disease relative to the surveillance of the overall count of disease cases across the entire study region. We introduce the surveillance conditional predictive ordinate as a general Bayesian model-based surveillance technique that allows us to detect small areas of increased disease incidence when spatial data are available. To address the problem of mult…

Factors Influencing Teachers’ Use of ICT in Class: Evidence from a Multilevel Logistic Model

2022

Information and Communication Technologies (ICTs) have become a key factor in the educational context, especially in the aftermath of the COVID-19 pandemic, and, correctly implemented, can help to improve academic performance. The aim of this research was to analyse the factors that influence teachers’ decisions to use ICT more- or less frequently to carry out tasks and exercises in their classes. To this end, we estimated a multilevel logistic model with census data from the individualized evaluation of students of the Community of Madrid (Spain) carried out at the end of the 2018–2019 academic year in primary and secondary education. Additionally, we applied multiple imputation techniques…

Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog

2021

Abbott, R., et al. (LIGO and Virgo Collaboration)

Multilevel Latent Profile Analysis With Covariates : Identifying Job Characteristics Profiles in Hierarchical Data as an Example

2018

Latent profile analysis (LPA) is a person-centered method commonly used in organizational research to identify homogeneous subpopulations of employees within a heterogeneous population. However, in the case of nested data structures, such as employees nested in work departments, multilevel techniques are needed. Multilevel LPA (MLPA) enables adequate modeling of subpopulations in hierarchical data sets. MLPA enables investigation of variability in the proportions of Level 1 profiles across Level 2 units, and of Level 2 latent classes based on the proportions of Level 1 latent profiles and Level 1 ratings, and the extent to which covariates drawn from the different hierarchical levels of the…

Using the hierarchical modeling approach to derive spatial distribution of precipitation and temperature datasets. A case study for the area of Sicil…

2013

The interest for spatial interpolating climatic variables available by means of point measurements, as precipitation and temperature, arises from different needs, ranging from their usage for hydrological models to the reconstruction of climatic atlas of spatially distributed data. In some areas the spatial distribution of these variables can be related to the extremely variable morphology of the area. While simple deterministic interpolation methods usually produce just the spatial distribution of the variable of interest, implicitly relying on the spatial autocorrelation and manually tuning a few parameters, more complex statistical models, are able to derive the uncertainty associated wi…