Open Access
La necesidad de un manifiesto a favor de la alfabetización estadística: editorial
(Sociedad Estadística e Investigación Operativa (SEIO), 2025-03-27) Casals, Martí ; Daunis i Estadella, Pepus; Galé, Carmen; Goicoa Mangado, Tomás; Patino-Alonso, Carmen; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute for Advanced Materials and Mathematics - INAMAT2
Imagina leer el siguiente titular en un periódico: “Las personas que consumen café tienen un 50% menos de probabilidad de desarrollar ciertas enfermedades”. A partir de esta lectura, decides aumentar tu consumo diario de café. Sin embargo, antes de tomar esa decisión hay que conocer cómo se ha llegado a dicha conclusión: cuál es el tamaño de la muestra, el diseño del estudio, sobre qué población se aplica, el método de recolección de datos, y valorar si es posible establecer relaciones causales. Este ejemplo ilustra como la falta de conocimiento sobre el procedimiento puede comprometer la validez del estudio y se puede traducir en una interpretación incorrecta o unos resultados sesgados. Una comunicación deficiente puede llevar decisiones mal fundamentadas, incluso en áreas críticas como la salud y el bienestar (Spiegelhalter, 2019).
Open Access
Online relative risks/rates estimation in spatial and spatio-temporal disease mapping
(Elsevier, 2019) Adin Urtasun, Aritz; Goicoa Mangado, Tomás; Ugarte Martínez, María Dolores; Estatistika, Informatika eta Matematika; Institute for Advanced Materials and Mathematics - INAMAT2; Estadística, Informática y Matemáticas
Background and objective: Spatial and spatio-temporal analyses of count data are crucial in epidemiology and other fields to unveil spatial and spatio-temporal patterns of incidence and/or mortality risks. However, fitting spatial and spatio-temporal models is not easy for non-expert users. The objective of this paper is to present an interactive and user-friendly web application (named SSTCDapp) for the analysis of spatial and spatio-temporal mortality or incidence data. Although SSTCDapp is simple to use, the underlying statistical theory is well founded and all key issues such as model identifiability, model selection, and several spatial priors and hyperpriors for sensitivity analyses are properly addressed. Methods: The web application is designed to fit an extensive range of fairly complex spatio-temporal models to smooth the very often extremely variable standardized incidence/mortality risks or crude rates. The application is built with the R package shiny and relies on the well founded integrated nested Laplace approximation technique for model fitting and inference. Results: The use of the web application is shown through the analysis of Spanish spatio-temporal breast cancer data. Different possibilities for the analysis regarding the type of model, model selection criteria, and a range of graphical as well as numerical outputs are provided. Conclusions: Unlike other software used in disease mapping, SSTCDapp facilitates the fit of complex statistical models to non-experts users without the need of installing any software in their own computers, since all the analyses and computations are made in a powerful remote server. In addition, a desktop version is also available to run the application locally in those cases in which data confidentiality is a serious issue.
Open Access
A two-stage approach to estimate spatial and spatio-temporal disease risks in the presence of local discontinuities and clusters
(SAGE, 2018-04-13) Adin Urtasun, Aritz; Lee, Duncan; Goicoa Mangado, Tomás; Ugarte Martínez, María Dolores; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute for Advanced Materials and Mathematics - INAMAT2
Disease risk maps for areal unit data are often estimated from Poisson mixed models with local spatial smoothing, for example by incorporating random effects with a conditional autoregressive prior distribution. However, one of the limitations is that local discontinuities in the spatial pattern are not usually modelled, leading to over-smoothing of the risk maps and a masking of clusters of hot/coldspot areas. In this paper, we propose a novel two-stage approach to estimate and map disease risk in the presence of such local discontinuities and clusters. We propose approaches in both spatial and spatio-temporal domains, where for the latter the clusters can either be fixed or allowed to vary over time. In the first stage, we apply an agglomerative hierarchical clustering algorithm to training data to provide sets of potential clusters, and in the second stage, a two-level spatial or spatio-temporal model is applied to each potential cluster configuration. The superiority of the proposed approach with regard to a previous proposal is shown by simulation, and the methodology is applied to two important public health problems in Spain, namely stomach cancer mortality across Spain and brain cancer incidence in the Navarre and Basque Country regions of Spain.
Open Access
Bayesian inference in multivariate spatio-temporal areal models using INLA: analysis of gender-based violence in small areas
(Springer, 2020) Vicente Fuenzalida, Gonzalo; Goicoa Mangado, Tomás; Ugarte Martínez, María Dolores; Estatistika, Informatika eta Matematika; Institute for Advanced Materials and Mathematics - INAMAT2; Estadística, Informática y Matemáticas
Multivariate models for spatial count data are currently receiving attention in disease mapping to model two or more diseases jointly. They have been thoroughly studied from a theoretical point of view, but their use in practice is still limited because they are computationally expensive and, in general, they are not implemented in standard software to be used routinely. Here, a new multivariate proposal, based on the recently derived M models for spatial data, is developed for spatio-temporal areal data. The model takes account of the correlation between the spatial and temporal patterns of the phenomena being studied, and it also includes spatio-temporal interactions. Though multivariate models have been traditionally fitted using Markov chain Monte Carlo techniques, here we propose to adopt integrated nested Laplace approximations to speed up computations as results obtained using both fitting techniques were nearly identical. The techniques are used to analyse two forms of crimes against women in India. In particular, we focus on the joint analysis of rapes and dowry deaths in Uttar Pradesh, the most populated Indian state, during the years 2001-2014.
Open Access
Comments on: Modular regression - a Lego system for building structured additive distributional regression models with tensor product interactions
(Springer, 2019) Goicoa Mangado, Tomás; Estatistika, Informatika eta Matematika; Institute for Advanced Materials and Mathematics - INAMAT2; Estadística, Informática y Matemáticas
This paper comments the article 'Modular regression - a Lego system for building structured additive distributional regression models with tensor product interactions', where the authors address the important topic of building very general models with interaction terms facing the relevant issue of identifiability.
Open Access
The effect of changing temperature and agar concentration at proliferation stage in the final success of Aleppo pine somatic embryogenesis
(Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria (INIA), 2017) Pereira, Catia; Montalbán, Itziar A.; Goicoa Mangado, Tomás; Ugarte Martínez, María Dolores; Correia, Sandra; Canhoto, Jorge M.; Moncaleán, Paloma; Estadística e Investigación Operativa; Estatistika eta Ikerketa Operatiboa
Aim of the study: The effect of physical and chemical conditions at proliferation stage was evaluated in order to elucidate if this stage is the determinant phase to induce a marked effect in Pinus halepensis somatic embryogenesis. Area of study: The study was conducted in research laboratories of Neiker (Arkaute, Spain). Material and methods: Pinus halepensis embryonal masses from ten embryogenic cell lines subjected to nine treatments (tissues cultured at three temperatures on media supplemented with three agar concentrations) at proliferation stage. Main results: Significant differences were observed among different proliferation conditions months later at the end of maturation, germination and acclimatization stages. Research highlights: Aleppo pine embryonal masses are cultured under standard conditions on a culture medium supplemented with 4.5 g/L Gelrite® at 23ºC. However, better results in terms of plantlet production can be obtained proliferating the embryonal masses at 18ºC in a culture media with significantly lower water availability.
Open Access
High-dimensional order-free multivariate spatial disease mapping
(Springer, 2023) Vicente Fuenzalida, Gonzalo; Adin Urtasun, Aritz; Goicoa Mangado, Tomás; Ugarte Martínez, María Dolores; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute for Advanced Materials and Mathematics - INAMAT2; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, PJUPNA2001
Despite the amount of research on disease mapping in recent years, the use of multivariate models for areal spatial data remains limited due to difficulties in implementation and computational burden. These problems are exacerbated when the number of areas is very large. In this paper, we introduce an order-free multivariate scalable Bayesian modelling approach to smooth mortality (or incidence) risks of several diseases simultaneously. The proposal partitions the spatial domain into smaller subregions, fits multivariate models in each subdivision and obtains the posterior distribution of the relative risks across the entire spatial domain. The approach also provides posterior correlations among the spatial patterns of the diseases in each partition that are combined through a consensus Monte Carlo algorithm to obtain correlations for the whole study region. We implement the proposal using integrated nested Laplace approximations (INLA) in the R package bigDM and use it to jointly analyse colorectal, lung, and stomach cancer mortality data in Spanish municipalities. The new proposal allows for the analysis of large datasets and yields superior results compared to fitting a single multivariate model. Additionally, it facilitates statistical inference through local homogeneous models, which may be more appropriate than a global homogeneous model when dealing with a large number of areas.
Open Access
Temporal evolution of brain cancer incidence in the municipalities of Navarre and the Basque Country, Spain
(BioMed Central, 2015) Ugarte Martínez, María Dolores; Adin Urtasun, Aritz; Goicoa Mangado, Tomás; Casado, Itziar; Ardanaz, Eva; Larrañaga, Nerea; Estatistika eta Ikerketa Operatiboa; Institute for Advanced Materials and Mathematics - INAMAT2; Estadística e Investigación Operativa; Gobierno de Navarra / Nafarroako Gobernua: proyecto 113 Res. 2186/2014
Background: Brain cancer incidence rates in Spain are below the European’s average. However, there are two regions in the north of the country, Navarre and the Basque Country, ranked among the European regions with the highest incidence rates for both males and females. Our objective here was two-fold. Firstly, to describe the temporal evolution of the geographical pattern of brain cancer incidence in Navarre and the Basque Country, and secondly, to look for specific high risk areas (municipalities) within these two regions in the study period (1986–2008). Methods: A mixed Poisson model with two levels of spatial effects is used. The model also included two levels of spatial effects (municipalities and local health areas). Model fitting was carried out using penalized quasi-likelihood. High risk regions were detected using upper one-sided confidence intervals. Results: Results revealed a group of high risk areas surrounding Pamplona, the capital city of Navarre, and a few municipalities with significant high risks in the northern part of the region, specifically in the border between Navarre and the Basque Country (Gipuzkoa). The global temporal trend was found to be increasing. Differences were also observed among specific risk evolutions in certain municipalities. Conclusions: Brain cancer incidence in Navarre and the Basque Country (Spain) is still increasing with time. The number of high risk areas within those two regions is also increasing. Our study highlights the need of continuous surveillance of this cancer in the areas of high risk. However, due to the low percentage of cases explained by the known risk factors, primary prevention should be applied as a general recommendation in these populations.
Open Access
Evaluating recent methods to overcome spatial confounding
(Springer, 2022) Urdangarin Iztueta, Arantxa; Goicoa Mangado, Tomás; Ugarte Martínez, María Dolores; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute for Advanced Materials and Mathematics - INAMAT2; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
The concept of spatial confounding is closely connected to spatial regression, although no general definition has been established. A generally accepted idea of spatial confounding in spatial regression models is the change in fixed effects estimates that may occur when spatially correlated random effects collinear with the covariate are included in the model. Different methods have been proposed to alleviate spatial confounding in spatial linear regression models, but it is not clear if they provide correct fixed effects estimates. In this article, we consider some of those proposals to alleviate spatial confounding such as restricted regression, the spatial+ model, and transformed Gaussian Markov random fields. The objective is to determine which one provides the best estimates of the fixed effects. Dowry death data in Uttar Pradesh in 2001, stomach cancer incidence data in Slovenia in the period 1995–2001 and lip cancer incidence data in Scotland between the years 1975–1980 are analyzed. Several simulation studies are conducted to evaluate the performance of the methods in different scenarios of spatial confounding. Results reflect that the spatial+ method seems to provide fixed effects estimates closest to the true value although standard errors could be inflated
Open Access
Estimación del desempleo por comarcas en Navarra
(Gobierno de Navarra, Departamento de Economía y Hacienda, 2005) Ugarte Martínez, María Dolores; Militino, Ana F.; González Ramajo, Begoña; Goicoa Mangado, Tomás; Sagaseta López, M.; Estadística e Investigación Operativa; Estatistika eta Ikerketa Operatiboa
El conocimiento del desempleo en una región es un indicador potente del ritmo de crecimiento de una economía, ya que de forma indirecta mide su capacidad para generar empleo. El Instituto de Estadística de Navarra está apostando por proporcionar en un futuro cercano estimaciones del desempleo a un nivel cada vez más desagregado. La heterogeneidad de las comarcas navarras y el interés mostrado por administraciones locales y sindicatos, hace necesario tener un conocimiento de la situación de desempleo a nivel comarcal, evitando así descansar únicamente en el resultado global para toda Navarra tal y como lo proporciona la Encuesta de Población Activa (EPA). La tarea es compleja, pero está incardinada además en uno de los objetivos prioritarios del proyecto europeo EURAREA, del cual ha formado parte el Instituto Nacional de Estadística (INE), y por ende, el Instituto de Estadística de Navarra. Es decir, hay un interés real en Europa por proporcionar estimaciones a nivel comarcal. En Navarra esta tarea ya ha comenzado y en este congreso presentamos algunos de los resultados obtenidos. En particular se ilustran las estimaciones preliminares derivadas de la aplicación de diversos estimadores basados en el diseño para obtener la proporción de parados por sexo en las siete comarcas de Navarra. Se compara además el comportamiento de diversos estimadores en términos del sesgo relativo y del error cuadrático medio relativo. Los estimadores ofrecidos permiten calcular además la estimación del número de ocupados e inactivos, así como de sus correspondientes tasas.