0000000000610056
AUTHOR
Anabel Forte
Determinants of between-hospital variations in outcomes for patients admitted with COPD exacerbations: findings from a nationwide clinical audit (AUDIPOC) in Spain.
Background Previous studies have demonstrated significant variability in the processes of care and outcomes of chronic obstructive pulmonary disease (COPD) exacerbations. The AUDIPOC is a Spanish nationwide clinical audit that identified large between-hospital variations in care and clinical outcomes. Here, we test the hypothesis that these variations can be attributed to either patient characteristics, hospital characteristics and/or the so-called hospital-clustering effect, which indicates that patients with similar characteristics may experience different processes of care and outcomes depending on the hospital to which they are admitted. Methods A clinical audit of 5178 COPD patients co…
Short and Long-Term Trainability in Older Adults: Training and Detraining Following Two Years of Multicomponent Cognitive—Physical Exercise Training
Despite the benefits of multicomponent physical&ndash
Incidence and control of black spot syndrome of tiger nut
Tiger nut (Cyperus esculentum) is a very profitable crop in Valencia, Spain, but in the last years, part of the harvested tubers presents black spots in the skin making them unmarketable. Surveys performed in two consecutive years showed that about 10% of the tubers were severely affected by the black spot syndrome whose aetiology is unknown. Disease control procedures based on selection of tubers used as seed (seed tubers) or treatment with hot-water and/or chemicals were assayed in greenhouse. These assays showed that that this syndrome had a negative impact on the germination rate, tuber size and yield. Selection of asymptomatic seed tubers reduced drastically the incidence of the black …
Variable selection in the analysis of energy consumption-growth nexus
There is abundant empirical literature that focuses on whether energy consumption is a critical driver of economic growth. The evolution of this literature has largely consisted of attempts to solve the problems and answer the criticisms arising from earlier studies. One of the most common criticisms is that previous work concentrates on the bivariate relationship, energy consumption–economic growth. Many authors try to overcome this critique using control variables. However, the choice of these variables has been ad hoc, made according to the subjective economic rationale of the authors. Our contribution to this literature is to apply a robust probabilistic model to select the explanatory …
Sequential Monte Carlo Methods in Random Intercept Models for Longitudinal Data
Longitudinal modelling is common in the field of Biostatistical research. In some studies, it becomes mandatory to update posterior distributions based on new data in order to perform inferential process on-line. In such situations, the use of posterior distribution as the prior distribution in the new application of the Bayes’ theorem is sensible. However, the analytic form of the posterior distribution is not always available and we only have an approximated sample of it, thus making the process “not-so-easy”. Equivalent inferences could be obtained through a Bayesian inferential process based on the set that integrates the old and new data. Nevertheless, this is not always a real alterna…
Bayesian joint modeling of bivariate longitudinal and competing risks data: An application to study patient-ventilator asynchronies in critical care patients
Mechanical ventilation is a common procedure of life support in intensive care. Patient-ventilator asynchronies (PVAs) occur when the timing of the ventilator cycle is not simultaneous with the timing of the patient respiratory cycle. The association between severity markers and the events death or alive discharge has been acknowledged before, however, little is known about the addition of PVAs data to the analyses. We used an index of asynchronies (AI) to measure PVAs and the SOFA (sequential organ failure assessment) score to assess overall severity. To investigate the added value of including the AI, we propose a Bayesian joint model of bivariate longitudinal and competing risks data. Th…
The geography of Spanish bank branches
This article analyzes the determinants of bank branch location in Spain taking the role of geography explicitly into account. After a long period of intense territorial expansion, especially by savings banks, many of these firms are now involved in merger processes triggered off by the financial crisis, most of which entail the closing of many branches. However, given the contributions of this type of banks to limit financial exclusion, this process might exacerbate the consequences of the crisis for some disadvantaged social groups. Related problems such as new banking regulation initiatives (Basel III), or the current excess capacity in the sector add further relevance to this problem. We…
Practical Issues on Energy-Growth Nexus Data and Variable Selection With Bayesian Analysis
Abstract Given that the energy-growth nexus (EGN) is short of a complete theoretical base, the production function used therein is typically complemented with numerous variables that characterize an economy. Researchers are often puzzled not only with the selection of variables per se, but also with the variable sources and the various data handlings which become apparent and available only after years of experience in this research field. Thus, this chapter is divided into two distinctive parts: The first part contains an overview of the available data sources for the EGN as well as a succinct selection of advice on data handlings, transformations, and interpretations that could come handy…
An Ordinal Joint Model for Breast Cancer
We propose a Bayesian joint model to analyze the association between longitudinal measurements of an ordinal marker and time to a relevant event. The longitudinal process is defined in terms of a proportional-odds cumulative logit model and the time-to-event process through a left-truncated Cox proportional hazards model with information of the longitudinal marker and baseline covariates. Both longitudinal and survival processes are connected by a common vector of random effects.
Frequentist and Bayesian approaches for a joint model for prostate cancer risk and longitudinal prostate-specific antigen data
The paper describes the use of frequentist and Bayesian shared-parameter joint models of longitudinal measurements of prostate-specific antigen (PSA) and the risk of prostate cancer (PCa). The motivating dataset corresponds to the screening arm of the Spanish branch of the European Randomized Screening for Prostate Cancer study. The results show that PSA is highly associated with the risk of being diagnosed with PCa and that there is an age-varying effect of PSA on PCa risk. Both the frequentist and Bayesian paradigms produced very close parameter estimates and subsequent 95% confidence and credibility intervals. Dynamic estimations of disease-free probabilities obtained using Bayesian infe…
BayesVarSel: Bayesian Testing, Variable Selection and model averaging in Linear Models using R
This paper introduces the R package BayesVarSel which implements objective Bayesian methodology for hypothesis testing and variable selection in linear models. The package computes posterior probabilities of the competing hypotheses/models and provides a suite of tools, specifically proposed in the literature, to properly summarize the results. Additionally, \ourpack\ is armed with functions to compute several types of model averaging estimations and predictions with weights given by the posterior probabilities. BayesVarSel contains exact algorithms to perform fast computations in problems of small to moderate size and heuristic sampling methods to solve large problems. The software is inte…
Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data
The statistical analysis of the information generated by medical follow-up is a very important challenge in the field of personalized medicine. As the evolutionary course of a patient's disease progresses, his/her medical follow-up generates more and more information that should be processed immediately in order to review and update his/her prognosis and treatment. Hence, we focus on this update process through sequential inference methods for joint models of longitudinal and time-to-event data from a Bayesian perspective. More specifically, we propose the use of sequential Monte Carlo (SMC) methods for static parameter joint models with the intention of reducing computational time in each…
Criteria for Bayesian model choice with application to variable selection
In objective Bayesian model selection, no single criterion has emerged as dominant in defining objective prior distributions. Indeed, many criteria have been separately proposed and utilized to propose differing prior choices. We first formalize the most general and compelling of the various criteria that have been suggested, together with a new criterion. We then illustrate the potential of these criteria in determining objective model selection priors by considering their application to the problem of variable selection in normal linear models. This results in a new model selection objective prior with a number of compelling properties.
Efecto de la retroalimentación orientada al acierto: un caso de estudio de analítica del aprendizaje
La Analítica de datos en Educación se puede definir como el área encargada de medir, recopilar y analizar conjuntos de datos obtenidos mediante el uso de entornos tecnológicos de aprendizaje o plataformas de aprendizaje asistido por computadora que permiten registrar las interacciones o trazas digitales del estudiantado. En particular, el estudio de la traza digital registrada puede contribuir positivamente en la comprensión de las estrategias seguidas por el estudiantado al resolver una tarea. En este trabajo se presenta un caso de estudio exploratorio en el que analiza el posible impacto del uso de la retroalimentación orientada al acierto mediante el uso de un entorno tecnológico con el …
Does social capital matter for European regional growth?
Abstract This paper analyzes the role of different elements of social capital in economic growth for a sample of 85 European regions during the period 1995–2008. Despite the remarkable progress that social capital and European regional economic growth literatures have experienced over the last two decades, initiatives combining the two are few, and entirely yet to come for the post-1990s period. Recent improvements in data availability allow this gap in the literature to be closed, since they enable the researcher to consider the traditionally disregarded Eastern and Central European (ECE) regions. This is particularly interesting, as they are all transition economies that recently joined t…
A Trans-Omics Comparison Reveals Common Gene Expression Strategies in Four Model Organisms and Exposes Similarities and Differences between Them.
AbstractThe ultimate goal of gene regulation should focus on the protein level. However, as mRNA is an obligate intermediary, and because the amounts of mRNAs and proteins are controlled by their synthesis and degradation rates, the cellular amount of a given protein can be attained following different strategies. By studying omics datasets for six expression variables (mRNA and protein amounts, plus their synthesis and decay rates), we previously demonstrated the existence of common expression strategies (CES) for functionally-related genes in the yeastSaccharomyces cerevisiae. Here we extend that study to two other eukaryotes: the distantly related yeastSchizosaccharomyces pombeand cultur…
Bayesian joint modeling for assessing the progression of chronic kidney disease in children.
Joint models are rich and flexible models for analyzing longitudinal data with nonignorable missing data mechanisms. This article proposes a Bayesian random-effects joint model to assess the evolution of a longitudinal process in terms of a linear mixed-effects model that accounts for heterogeneity between the subjects, serial correlation, and measurement error. Dropout is modeled in terms of a survival model with competing risks and left truncation. The model is applied to data coming from ReVaPIR, a project involving children with chronic kidney disease whose evolution is mainly assessed through longitudinal measurements of glomerular filtration rate.
Bayesian joint ordinal and survival modeling for breast cancer risk assessment
We propose a joint model to analyze the structure and intensity of the association between longitudinal measurements of an ordinal marker and time to a relevant event. The longitudinal process is defined in terms of a proportional-odds cumulative logit model. Time-to-event is modeled through a left-truncated proportionalhazards model, which incorporates information of the longitudinal marker as well as baseline covariates. Both longitudinal and survival processes are connected by means of a common vector of random effects. General inferences are discussed under the Bayesian approach and include the posterior distribution of the probabilities associated to each longitudinal category and the …
Girls4STEM: Gender Diversity in STEM for a Sustainable Future
Science, Technology, Engineering, and Mathematics (STEM) are key disciplines towards tackling the challenges related to the Sustainable Development Goals. However, evidence shows that women are enrolling in these disciplines in a smaller percentage than men, especially in Engineering related fields. As stated by the United Nations Women section, increasing the number of women studying and working in STEM fields is fundamental towards achieving better solutions to the global challenges, since the potential for innovation is larger. In this paper, we present the Girls4STEM project, which started in 2019 at the Escola Tè
Methods and Tools for Bayesian Variable Selection and Model Averaging in Normal Linear Regression
In this paper, we briefly review the main methodological aspects concerned with the application of the Bayesian approach to model choice and model averaging in the context of variable selection in regression models. This includes prior elicitation, summaries of the posterior distribution and computational strategies. We then examine and compare various publicly available R-packages, summarizing and explaining the differences between packages and giving recommendations for applied users. We find that all packages reviewed (can) lead to very similar results, but there are potentially important differences in flexibility and efficiency of the packages.
Determinants of dynamic inspiratory muscle strength in healthy trained elderly.
Background: The S-Index assessed by means of electronic devices is a measure of Inspiratory Muscle Strength (IMS) that highly correlates with the maximal inspiratory pressure (MIP). The variables involved when using regression models for the prediction of IMS/MIP depend on both the sample characteristics and the device or protocol used. In light of the scarce information on the influence of physical activity (PA) on IMS in healthy older adults (OA), together with the incorporation of new assessment devices, the objectives of this research are: 1) to determine which factors influence the IMS in a group of trained OA, using a portable electronic device; and 2) to propose a regression model to…
Geographical variation in pharmacological prescription
Promoting rational drug administration in treatments is one of the most important issues in Public Health. Bayesian hierarchical models are a very useful tool for incorporating geographical information into the analysis of pharmacological prescription data. They allow the mapping of spatial components which express the trend of geographical variation. In addition, these models are able to deal with uncertainty in a sequential way through prior distributions on parameters and hyperparameters. Bayes' theorem combines all types of information and provides the posterior distribution which is computed through Markov Chain Monte Carlo (MCMC) simulation methods. Simulated data for pharmacological …
Subsurface swimming and stationary diving are metabolically cheap in adult Pacific walruses (Odobenus rosmarus divergens).
ABSTRACT Walruses rely on sea-ice to efficiently forage and rest between diving bouts while maintaining proximity to prime foraging habitat. Recent declines in summer sea ice have resulted in walruses hauling out on land where they have to travel farther to access productive benthic habitat while potentially increasing energetic costs. Despite the need to better understand the impact of sea ice loss on energy expenditure, knowledge about metabolic demands of specific behaviours in walruses is scarce. In the present study, 3 adult female Pacific walruses (Odobenus rosmarus divergens) housed in professional care participated in flow-through respirometry trials to measure metabolic rates while…
What Does Objective Mean in a Dirichlet-multinomial Process?
Summary The Dirichlet-multinomial process can be seen as the generalisation of the binomial model with beta prior distribution when the number of categories is larger than two. In such a scenario, setting informative prior distributions when the number of categories is great becomes difficult, so the need for an objective approach arises. However, what does objective mean in the Dirichlet-multinomial process? To deal with this question, we study the sensitivity of the posterior distribution to the choice of an objective Dirichlet prior from those presented in the available literature. We illustrate the impact of the selection of the prior distribution in several scenarios and discuss the mo…
Towards breaking the Gender Gap in Science, Technology, Engineering and Mathematics
The gender gap in Science, Technology, Engineering and Mathematics (STEM) has drawn the attention of research and academic communities due to its impact in the Digital Society, targeting the fourth and fifth 2030 sustainable development goals of achieving quality education and gender equality. Recent studies show that women are enrolling STEM studies in smaller proportion than men and that they have a larger probability to renounce to their jobs or to take leaves. In this scenario, the involvement of educational institutions is seminal to change this trend. The School of Engineering of the University of Valencia (ETSE-UV), Spain, launched in 2011 a pilot program to promote STEM careers, foc…
Spatial analysis of bovine spongiform encephalopathy in Galicia, Spain (2000–2005)
Abstract In Spain, the first bovine spongiform encephalopathy (BSE) case was detected in 2000 in a cow born in the Galicia region (Northwestern Spain). From then and until October 2005, 590 cases were detected, 223 of them in Galicia. In 1994, meat and bone meal (MBM) was banned on ruminant feed and, in 1996, an EU decision mandating an overall change in MBM processing was implemented. This decision was gradually applied in the territory and not enforced before July 1998. The objective of this study was to explore clustering of BSE cases and estimate the standard incidence ratio (SIR) of BSE in Galicia. Our study was based on the BSE cases detected during the surveillance period 2000–2005 i…
Bayesian longitudinal models for paediatric kidney transplant recipients
Chronic kidney disease is a progressive loss of renal function which results in the inability of the kidneys to properly filter waste from the blood. Renal function is usually estimated by the glomerular filtration rate (eGFR), which decreases with the worsening of the disease. Bayesian longitudinal models with covariates, random effects, serial correlation and measurement error are discussed to analyse the progression of eGFR in first transplanted children taken from a study in Valencia, Spain.