Estimating vadose zone hydraulic properties using ground penetrating radar: The impact of prior information

A number of geophysical methods, such as ground-penetrating radar (GPR), have the potential to provide valuable information on hydrological properties in the unsaturated zone. In particular, the stochastic inversion of such data within a coupled geophysical-hydrological framework may allow for the effective estimation of vadose zone hydraulic parameters and their corresponding uncertainties. A critical issue in stochastic inversion is choosing prior parameter probability distributions from which potential model configurations are drawn and tested against observed data. A well chosen prior should reflect as honestly as possible the initial state of knowledge regarding the parameters and be neither overly specific nor too conservative. In a Bayesian context, combining the prior with available data yields a posterior state of knowledge about the parameters, which can then be used statistically for predictions and risk assessment. Here we investigate the influence of prior information regarding the van Genuchten-Mualem (VGM) parameters, which describe vadose zone hydraulic properties, on the stochastic inversion of crosshole GPR data collected under steady state, natural-loading conditions. We do this using a Bayesian Markov chain Monte Carlo (MCMC) inversion approach, considering first noninformative uniform prior distributions and then more informative priors derived from soil property databases. For the informative priors, we further explore the effect of including information regarding parameter correlation. Analysis of both synthetic and field data indicates that the geophysical data alone contain valuable information regarding the VGM parameters. However, significantly better results are obtained when we combine these data with a realistic, informative prior.

Official Positions for FRAX® clinical regarding prior fractures from Joint Official Positions Development Conference of the International Society for Clinical Densitometry and International Osteoporosis Foundation on FRAX®.

The 2010 Position Development Conference addressed four questions related to the impact of previous fractures on 10-year fracture risk as calculated by FRAX(®). To address these questions, PubMed was searched on the keywords "fracture, epidemiology, osteoporosis." Titles of retrieved articles were reviewed for an indication that risk for future fracture was discussed. Abstracts of these articles were reviewed for an indication that one or more of the questions listed above was discussed. For those that did, the articles were reviewed in greater detail to extract the findings and to find additional past work and citing works that also bore on the questions. The official positions and the supporting literature review are presented here. FRAX(®) underestimates fracture probability in persons with a history of multiple fractures (good, A, W). FRAX(®) may underestimate fracture probability in individuals with prevalent severe vertebral fractures (good, A, W). While there is evidence that hip, vertebral, and humeral fractures appear to confer greater risk of subsequent fracture than fractures at other sites, quantification of this incremental risk in FRAX(®) is not possible (fair, B, W). FRAX(®) may underestimate fracture probability in individuals with a parental history of non-hip fragility fracture (fair, B, W). Limitations of the methodology include performance by a single reviewer, preliminary review of the literature being confined to titles, and secondary review being limited to abstracts. Limitations of the evidence base include publication bias, overrepresentation of persons of European descent in the published studies, and technical differences in the methods used to identify prevalent and incident fractures. Emerging topics for future research include fracture epidemiology in non-European populations and men, the impact of fractures in family members other than parents, and the genetic contribution to fracture risk.

The modulation of simple reaction time by the spatial probability of a visual stimulus

Simple reaction time (SRT) in response to visual stimuli can be influenced by many stimulus features. The speed and accuracy with which observers respond to a visual stimulus may be improved by prior knowledge about the stimulus location, which can be obtained by manipulating the spatial probability of the stimulus. However, when higher spatial probability is achieved by holding constant the stimulus location throughout successive trials, the resulting improvement in performance can also be due to local sensory facilitation caused by the recurrent spatial location of a visual target (position priming). The main objective of the present investigation was to quantitatively evaluate the modulation of SRT by the spatial probability structure of a visual stimulus. In two experiments the volunteers had to respond as quickly as possible to the visual target presented on a computer screen by pressing an optic key with the index finger of the dominant hand. Experiment 1 (N = 14) investigated how SRT changed as a function of both the different levels of spatial probability and the subject's explicit knowledge about the precise probability structure of visual stimulation. We found a gradual decrease in SRT with increasing spatial probability of a visual target regardless of the observer's previous knowledge concerning the spatial probability of the stimulus. Error rates, below 2%, were independent of the spatial probability structure of the visual stimulus, suggesting the absence of a speed-accuracy trade-off. Experiment 2 (N = 12) examined whether changes in SRT in response to a spatially recurrent visual target might be accounted for simply by sensory and temporally local facilitation. The findings indicated that the decrease in SRT brought about by a spatially recurrent target was associated with its spatial predictability, and could not be accounted for solely in terms of sensory priming.

Evaluating raw ensembles with the continuous ranked probability score

The continuous ranked probability score (CRPS) is a frequently used scoring rule. In contrast with many other scoring rules, the CRPS evaluates cumulative distribution functions. An ensemble of forecasts can easily be converted into a piecewise constant cumulative distribution function with steps at the ensemble members. This renders the CRPS a convenient scoring rule for the evaluation of ‘raw’ ensembles, obviating the need for sophisticated ensemble model output statistics or dressing methods prior to evaluation. In this article, a relation between the CRPS score and the quantile score is established. The evaluation of ‘raw’ ensembles using the CRPS is discussed in this light. It is shown that latent in this evaluation is an interpretation of the ensemble as quantiles but with non-uniform levels. This needs to be taken into account if the ensemble is evaluated further, for example with rank histograms.

The probability of sale and price premiums in withdrawn auctioned properties

This paper examines the impact of the auction process of residential properties that whilst unsuccessful at auction sold subsequently. The empirical analysis considers both the probability of sale and the premium of the subsequent sale price over the guide price, reserve and opening bid. The findings highlight that the final achieved sale price is influenced by key price variables revealed both prior to and during the auction itself. Factors such as auction participation, the number of individual bidders and the number of bids are significant in a number of the alternative specifications.

The probability of sale and price premiums in withdrawn auctioned properties

This paper examines the impact of the auction process of residential properties that whilst unsuccessful at auction sold subsequently. The empirical analysis considers both the probability of sale and the premium of the subsequent sale price over the guide price, reserve and opening bid. The findings highlight that the final achieved sale price is influenced by key price variables revealed both prior to and during the auction itself. Factors such as auction participation, the number of individual bidders and the number of bids are significant in a number of the alternative specifications.

Use of the probability of stone formation (PSF) score to assess stone forming risk and treatment response in a cohort of Brazilian stone formers

Introduction: The aim was to confirm that PSF (probability of stone formation) changed appropriately following medical therapy on recurrent stone formers.Materials and Methods: Data were collected on 26 Brazilian stone-formers. A baseline 24-hour urine collection was performed prior to treatment. Details of the medical treatment initiated for stone-disease were recorded. A PSF calculation was performed on the 24 hour urine sample using the 7 urinary parameters required: voided volume, oxalate, calcium, urate, pH, citrate and magnesium. A repeat 24-hour urine sample was performed for PSF calculation after treatment. Comparison was made between the PSF scores before and during treatment.Results: At baseline, 20 of the 26 patients (77%) had a high PSF score (> 0.5). Of the 26 patients, 17 (65%) showed an overall reduction in their PSF profiles with a medical treatment regimen. Eleven patients (42%) changed from a high risk (PSF > 0.5) to a low risk (PSF < 0.5) and 6 patients reduced their risk score but did not change risk category. Six (23%) patients remained in a high risk category (> 0.5) during both assessments.Conclusions: The PSF score reduced following medical treatment in the majority of patients in this cohort.

Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.

Using Prior Information from the Medical Literature in GWAS of Oral Cancer Identifies Novel Susceptibility Variant on Chromosome 4-the AdAPT Method

Background: Genome-wide association studies (GWAS) require large sample sizes to obtain adequate statistical power, but it may be possible to increase the power by incorporating complementary data. In this study we investigated the feasibility of automatically retrieving information from the medical literature and leveraging this information in GWAS. Methods: We developed a method that searches through PubMed abstracts for pre-assigned keywords and key concepts, and uses this information to assign prior probabilities of association for each single nucleotide polymorphism (SNP) with the phenotype of interest - the Adjusting Association Priors with Text (AdAPT) method. Association results from a GWAS can subsequently be ranked in the context of these priors using the Bayes False Discovery Probability (BFDP) framework. We initially tested AdAPT by comparing rankings of known susceptibility alleles in a previous lung cancer GWAS, and subsequently applied it in a two-phase GWAS of oral cancer. Results: Known lung cancer susceptibility SNPs were consistently ranked higher by AdAPT BFDPs than by p-values. In the oral cancer GWAS, we sought to replicate the top five SNPs as ranked by AdAPT BFDPs, of which rs991316, located in the ADH gene region of 4q23, displayed a statistically significant association with oral cancer risk in the replication phase (per-rare-allele log additive p-value [p(trend)] = 2.5 x 10(-3)). The combined OR for having one additional rare allele was 0.83 (95% CI: 0.76-0.90), and this association was independent of previously identified susceptibility SNPs that are associated with overall UADT cancer in this gene region. We also investigated if rs991316 was associated with other cancers of the upper aerodigestive tract (UADT), but no additional association signal was found. Conclusion: This study highlights the potential utility of systematically incorporating prior knowledge from the medical literature in genome-wide analyses using the AdAPT methodology. AdAPT is available online (url: http://services.gate.ac.uk/lld/gwas/service/config).

Placement year academic benefit revisited:effects of demographics, prior achievement and degree programme

Investigations of whether students taking undergraduate work placements show greater academic improvement than those who do not have shown inconsistent results. In most studies, sample sizes have been relatively small and few studies have taken into account pre-existing student differences.Here data from over 6000 students at one university over six cohorts and a range of programmes are analysed. Consistent academic benefit from placement experience, regardless of ethnicity, gender, socioeconomic background and subject is shown. However the impact of demographic factors on both achievement and on the probability of taking a placement suggests that future research should take these factors into account. The role of placements in promoting employability is contextualised as a secondary benefit to the primary goal of educating the mind in the Newman (1852) tradition. Possible causes of, and further research into, the improved academic performance identified are discussed.

Bayesian analysis of a mastitis control plan to investigate the influence of veterinary prior beliefs on clinical interpretation

The fundamental objective for health research is to determine whether changes should be made to clinical decisions. Decisions made by veterinary surgeons in the light of new research evidence are known to be influenced by their prior beliefs, especially their initial opinions about the plausibility of possible results. In this paper, clinical trial results for a bovine mastitis control plan were evaluated within a Bayesian context, to incorporate a community of prior distributions that represented a spectrum of clinical prior beliefs. The aim was to quantify the effect of veterinary surgeons’ initial viewpoints on the interpretation of the trial results. A Bayesian analysis was conducted using Markov chain Monte Carlo procedures. Stochastic models included a financial cost attributed to a change in clinical mastitis following implementation of the control plan. Prior distributions were incorporated that covered a realistic range of possible clinical viewpoints, including scepticism, enthusiasm and uncertainty. Posterior distributions revealed important differences in the financial gain that clinicians with different starting viewpoints would anticipate from the mastitis control plan, given the actual research results. For example, a severe sceptic would ascribe a probability of 0.50 for a return of <£5 per cow in an average herd that implemented the plan, whereas an enthusiast would ascribe this probability for a return of >£20 per cow. Simulations using increased trial sizes indicated that if the original study was four times as large, an initial sceptic would be more convinced about the efficacy of the control plan but would still anticipate less financial return than an initial enthusiast would anticipate after the original study. In conclusion, it is possible to estimate how clinicians’ prior beliefs influence their interpretation of research evidence. Further research on the extent to which different interpretations of evidence result in changes to clinical practice would be worthwhile.

Statistical learning of random probability measures

The study of random probability measures is a lively research topic that has attracted interest from different fields in recent years. In this thesis, we consider random probability measures in the context of Bayesian nonparametrics, where the law of a random probability measure is used as prior distribution, and in the context of distributional data analysis, where the goal is to perform inference given avsample from the law of a random probability measure. The contributions contained in this thesis can be subdivided according to three different topics: (i) the use of almost surely discrete repulsive random measures (i.e., whose support points are well separated) for Bayesian model-based clustering, (ii) the proposal of new laws for collections of random probability measures for Bayesian density estimation of partially exchangeable data subdivided into different groups, and (iii) the study of principal component analysis and regression models for probability distributions seen as elements of the 2-Wasserstein space. Specifically, for point (i) above we propose an efficient Markov chain Monte Carlo algorithm for posterior inference, which sidesteps the need of split-merge reversible jump moves typically associated with poor performance, we propose a model for clustering high-dimensional data by introducing a novel class of anisotropic determinantal point processes, and study the distributional properties of the repulsive measures, shedding light on important theoretical results which enable more principled prior elicitation and more efficient posterior simulation algorithms. For point (ii) above, we consider several models suitable for clustering homogeneous populations, inducing spatial dependence across groups of data, extracting the characteristic traits common to all the data-groups, and propose a novel vector autoregressive model to study of growth curves of Singaporean kids. Finally, for point (iii), we propose a novel class of projected statistical methods for distributional data analysis for measures on the real line and on the unit-circle.

One Step Forward: Contrasting The Effects Of Toe Clipping And Pit Tagging On Frog Survival And Recapture Probability.

Amphibians have been declining worldwide and the comprehension of the threats that they face could be improved by using mark-recapture models to estimate vital rates of natural populations. Recently, the consequences of marking amphibians have been under discussion and the effects of toe clipping on survival are debatable, although it is still the most common technique for individually identifying amphibians. The passive integrated transponder (PIT tag) is an alternative technique, but comparisons among marking techniques in free-ranging populations are still lacking. We compared these two marking techniques using mark-recapture models to estimate apparent survival and recapture probability of a neotropical population of the blacksmith tree frog, Hypsiboas faber. We tested the effects of marking technique and number of toe pads removed while controlling for sex. Survival was similar among groups, although slightly decreased from individuals with one toe pad removed, to individuals with two and three toe pads removed, and finally to PIT-tagged individuals. No sex differences were detected. Recapture probability slightly increased with the number of toe pads removed and was the lowest for PIT-tagged individuals. Sex was an important predictor for recapture probability, with males being nearly five times more likely to be recaptured. Potential negative effects of both techniques may include reduced locomotion and high stress levels. We recommend the use of covariates in models to better understand the effects of marking techniques on frogs. Accounting for the effect of the technique on the results should be considered, because most techniques may reduce survival. Based on our results, but also on logistical and cost issues associated with PIT tagging, we suggest the use of toe clipping with anurans like the blacksmith tree frog.

Prevalência de deficiência auditiva referida e causas atribuídas: um estudo de base populacional

Objetivou-se verificar a prevalência de deficiência auditiva referida pela população urbana de quatro localidades do Estado de São Paulo, Brasil, e estudar as causas atribuídas e variáveis sócio-demográficas. Foi realizado um estudo transversal de base populacional com dados referentes à população com 12 anos ou mais residente nas quatro localidades, em 2001 e 2002. Participaram 5.250 sujeitos selecionados por amostragem probabilística, estratificada e selecionada por conglomerados, em dois estágios. A análise dos dados foi exploratória, incluindo análise bivariada e regressão logística múltipla. A prevalência de deficiência auditiva foi 5,21%, mais acentuada nas faixas etárias acima de 59 anos (18,7%), que referiram doenças nos 15 dias anteriores à entrevista (8,4%), com transtorno mental comum (8,85%) e que fizeram uso de medicamentos nos últimos 3 dias (8,45%). O estudo dos fatores que se associam à deficiência auditiva direcionam intervenções de saúde para que atendam as reais necessidades da população, principalmente na atenção primária. Há necessidade de mais estudos populacionais com enfoque na audição, visto que esta é uma área escassa de publicações no Brasil.

Desigualdades no uso e acesso aos serviços de saúde entre idosos do município de São Paulo

OBJETIVO: Analisar os fatores relacionados à determinação e às desigualdades no acesso e uso dos serviços de saúde por idosos. MÉTODOS: Estudo integrante do Projeto Saúde, Bem-estar e Envelhecimento (SABE), no qual foram entrevistados 2.143 indivíduos com 60 anos ou mais no município de São Paulo, SP, em 2000. A amostra foi obtida em dois estágios, utilizando-se setores censitários com reposição, probabilidade proporcional à população e complementação da amostra de pessoas de 75 anos. Foi mensurado o uso de serviços hospitalares e ambulatoriais nos quatro meses anteriores à entrevista, relacionando-os com fatores de capacidade, necessidade e predisposição (renda total, escolaridade, seguro saúde, morbidade referida, auto-percepção, sexo e idade). O método estatístico utilizado foi regressão logística multivariada. RESULTADOS: Dos entrevistados, 4,7% referiram ter utilizado a internação hospitalar e 64,4% o atendimento ambulatorial. Dos atendimentos ambulatoriais em serviço público, 24,7% ocorreram em hospital e 24,1% em serviço ambulatorial; dentre os que ocorreram em serviços privados, 14,5% foram em hospital e 33,7% em clínicas. Pela análise multivariada, observou-se associação entre a utilização de serviços e sexo, presença de doenças, auto-percepção de saúde, interação da renda e escolaridade e posse de seguro saúde. A análise isolada com escolaridade apresentou efeito inverso. CONCLUSÕES: Foram observadas desigualdades no uso e acesso aos serviços de saúde e inadequação do modelo de atenção, indicando necessidade de políticas públicas que levem em conta as especificidades dessa população, facilitem o acesso e possam reduzir essas desigualdades.