1,721,087 research outputs found
lmviz
No full textA Package to Visualize Linear Models Features and Play with Them. Contains three shiny applications. Two are meant to explore linear model inference feature through simulation. The third is a game to learn interpreting diagnostic plots
Smoothing sample extremes: The mixed model approach
No full textNonparametric regression for sample extremes can be performed using a variety of
techniques. The penalized spline approach for the Poisson point process model is
considered. The generalized linear mixed model representation for the spline model, with
its Bayesian approach to inference, turns out to be a very flexible framework. Monte Carlo
Markov chain algorithms are employed for exploration of the posterior distribution. The
overall performance of the method is tested on simulated data. Two real data applications
are also discussed for modeling trend of intensity of earthquakes in Italy and for assessing
seasonality and short term trend of summer extreme temperatures in Milan, Italy
Statistical analysis of temperature impact on daily hospital admissions: analysis of data from Udine
No full textSummer Temperature Effects on Deaths and Hospital Admissions among Elderly Populations in two Italian Cities
No full text
A statistical approach to the relationship between temperature and health of local population
No full textAvoiding prior–data conflict in regression models via mixture priors
Full text linkThe Bayesian model consists of the prior–likelihood pair. A prior–data conflict arises whenever the prior allocates most of its mass to regions of the parameter space where the likelihood is relatively low. Once a prior–data conflict is diagnosed, what to do next is a hard question to answer. We propose an automatic prior elicitation that involves a two-component mixture of a diffuse and an informative prior distribution that favours the first component if a conflict emerges. Using various examples, we show that these mixture priors can be useful in regression models as a device for regularizing the estimates and retrieving useful inferential conclusions
Perceived neighbouhood quality and adult health status : new statistical advice useful to answer old questions?
No full textInterest in the quantitative effects of neighbourhood characteristics on adult health has recently increased . Particularly, investigations concern the statistical influence on health of several individual demographic and socioeconomic characteristics and of neighbourhood characteristics as perceived by respondents. We analyze these issues within an original conceptual framework and employing statistical models unusual in this context. We use data collected in the Los Angeles Family and Neighbourhood Survey (L.A.FANS) to model the number of hospital admissions occurred to each individual as a function of some individual and neighbourhood characteristics, the latter being related to the individual perceptions about the neighbourhood he lives in. We
employ generalized additive models with different istributional assumptions: Poisson,Negative Biomial and Z ro Inflated Poisson (ZIP). Such models allow us to estimate (through spline functions) potential non linear effects of the covariates on the response. Moreover, non standard representations are used to overcome difficulties in interpreting the results for ZIP models. It turns out that perceived neighbourhood characteristics, and in particular the perception of social cohesion, have a significant effect after controlling for individual characteristics relevant to hospital admissions frequency. From a modeling point of view ZIP and Negative binomial models prove to be superior to standard Poisson
model. We have confirmed the role of the neighbourhood where an individual lives in determining his health status. A strength of this analysis is that, due to the choice of the neighbourhood characteristics to be included in the model, the results do t depend of a particular definition of neighbourhood (which is traditionally based on
administrative boundaries), since each individual refers his perceptions to his personal definition of it
Bayesian composite marginal likelihoods
No full textThis paper proposes and discusses the use of composite marginal likelihoods for Bayesian inference. This approach allows one to deal with complex statistical models in the Bayesian framework, when the full likelihood - and thus the full posterior distribution - is impractical to compute or even analytically unknown.
The procedure is based on a suitable calibration of the composite likelihood
that yields the right asymptotic properties for the posterior probability distribution.
In this respect, an attractive technique is offered for important settings that at present are not easily tractable from a Bayesian perspective, such as, for instance, multivariate extreme value theory. Simulation studies and an application to multivariate extremes are analysed in detail
Statistical issues in choosing indicators to evaluate healthy cities projects (not only a political task)
No full textWe develop statistical considerations about methodologies that, at least in our opinion, are suitable to synthesize appropriately the impact on health of urban populations of socio-economic and environmental conditions and local policies.
In particular, we focus attention on the so called Health Impact Assessment (HIA) proposed by the European working group “Promoting and Supporting Integrated Approaches for Health and Sustainable Development at the Local Level across Europe” PHASE (2003-2005) within the World Health Organization (WHO) - Healthy Cities Project (HCP) (http://www.euro.who.int/healthy-cities/).
Among open issues about HCP in general and HIA in particular, we focus on statistical tools allowing for the multidimensionality of the phenomenon, the heterogeneity of its various aspects and the complexity of local urban realities involved. This will be done considering simultaneously both conceptual framework and data, measures and statistical models, trying to give policymakers and citizens relevant information in a suitable form as the HCP – Phase IV “Healthy Cities and Urban Governance” needs
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