1,721,154 research outputs found
Modeling psychophysical data at the population-level: the generalized linear mixed model
Full text linkMoscatelli A, Mezzetti M, Lacquaniti F. Modeling psychophysical data at the population-level: the generalized linear mixed model. Journal of Vision. 2012;12(11):1-17
A hierarchical Bayesian approach to age-specific back-calculation of cancer incidence rates
No full textA Bayesian hierarchical model for risk assessment of methylmercury
No full textThis article uses a Bayesian hierarchical model to quantify the adverse health effects associated with in-utero exposure to methylmercury. By allowing for study-to-study as well as outcome-to-outcome variability, the approach provides a useful meta-analytic tool for multi-outcome, multi-study environmental risk assessments. The analysis presented here expands on the findings of a National Academy of Sciences (NAS) committee, charged with advising the United States Environmental Protection Agency (EPA) on an appropriate approach to conducting a risk assessment for methylmercury. The NAS committee, for which the senior author (Ryan) was a committee member, reviewed the findings from several conflicting studies and reported the results from a Bayesian hierarchical model that synthesized information across several studies and for several outcomes. Although the NAS committee did not suggest that the hierarchical model be used as the actual basis for a methylmercury risk assessment, the results from the model were used to justify and support the final recommendation that the risk analysis be based on data from a study conducted in the Faroe Islands, which had found an association between in-utero exposure to methylmercury and impaired neurological development. We consider a variety of statistical issues, but particularly sensitivity to model specification. © 2003 American Statistical Association and the International Biometric Society
Interaction between inflammation and metabolism in periparturient dairy cows
No full textA large body of work has been conducted to elucidate the link between the loss of viability, sensitivity to pro-inflammatory mediators and the impairment of antimicrobial functions affecting the innate immune cells, the occurrence of uncontrolled inflammations, and the sudden alteration of the metabolism during the transition from pregnancy to lactation in highproducing dairy cows. Despite this massive effort, a clear link is still missing. The intent of this review is to summarize our current knowledge on the subject and attempt to propose a link. In the first part of this review we provide an overview of the physiological adaptation during the transition from pregnancy to lactation focusing on the alterations affecting the innate immune system and the inflammation occurring during this phase. In the second part of the review, we propose a relationship between the function of the innate immune system, the inflammatory conditions, and the metabolism in dairy cows during the transition from pregnancy to lactation with the intent to elucidate the driving cause of immune alterations occurring in this phase. In the third and final part, we review some novel dietary strategies to optimize the function of the innate immunity in dairy cows describing their mode of action and their applicability as an aid for dairy cows during the peripartal phase
Non parametric estimation of survival functions by means of partial exchangeability structures.
No full textBayesian factor analysis for spatially correlated data: application to cancer incidence data in Scotland 2012
Full text linkA hierarchical Bayesian factor model for multivariate spatially correlated data is proposed. Multiple cancer incidence data in Scotland are jointly analyzed, looking for common components, able to detect etiological factors of diseases hidden behind the data. The proposed method searches factor scores incorporating a dependence within observations due to a geographical structure. The great flexibility of the Bayesian approach allows the inclusion of prior opinions about adjacent regions having highly correlated observable and latent variables. The proposed model is an extension of a model proposed by Rowe (2003a) and starts from the introduction of separable covariance matrix for the observations. A Gibbs sampling algorithm is implemented to sample from the posterior distributions
Il Masieri Memorial a Venezia di F.Ll Wright, 1953-54
No full textLa ricerca presentata è relativa all'analisi geometrica e ricostruzione digitale del progetto per il Masieri Memorial di F.L. Wright a Venezia. In particolare sono state considerate tutte le fonti documentarie che hanno permesso di ricostruire le tre versioni del progetto, nella forma del modello digitale. I tre modelli sono pertanto stati comparati ed è stata fatta anche un'indagine sulla percezione di questo edificio e sull'impatto ambientale che avrebbe avuto nel contesto veneziano. Oltre alla ricostruzione digitale è stata predisposta anche una costruzione fisica del modello della facciata su Canal Grande, utilizzando le tecniche di sinterizzazione di polveri di nylon al laser
Combining individual and aggregated data to investigate the role of socioeconomic disparities on cancer burden in Italy
No full textQuantifying socioeconomic disparities and understanding the roots of inequalities are growing topics in cancer research. However, socioeconomic differences are challenging to investigate mainly due to the lack of accurate data at individual-level, while aggregate indicators are only partially informative. We implemented a multiple imputation algorithm within a statistical matching framework that combines diverse sources of data to estimate individual-level associations between income and risk of breast and lung cancer, adjusting for potential confounding factors in Italy. The framework is computationally flexible and can be adapted to similar contexts
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