On the optimism correction of the area under the receiver operating characteristic curve in logistic prediction models

When the same data are used to fit a model and estimate its predictive performance, this estimate may be optimistic, and its correction is required. The aim of this work is to compare the behaviour of different methods proposed in the literature when correcting for the optimism of the estimated area under the receiver operating characteristic curve in logistic regression models. A simulation study (where the theoretical model is known) is conducted considering different number of covariates, sample size, prevalence and correlation among covariates. The results suggest the use of k-fold cross-validation with replication and bootstrap.Peer Reviewe

Fast algorithm for smoothing parameter selection in multidimensional generalized P-splines

A new computational algorithm for estimating the smoothing parameters of a multidimensional penalized spline generalized model with anisotropic penalty is presented. This new proposal is based on the mixed model representation of a multidimensional P-spline, in which the smoothing parameter for each covariate is expressed in terms of variance components. On the basis of penalized quasi-likelihood methods (PQL), closed-form expressions for the estimates of the variance components are obtained. This formulation leads to an efficient implementation that can considerably reduce the computational load. The proposed algorithm can be seen as a generalization of the algorithm by Schall (1991) - for variance components estimation - to deal with non-standard structures of the covariance matrix of the random effects. The practical performance of the proposed computational algorithm is evaluated by means of simulations, and comparisons with alternative methods are made on the basis of the mean square error criterion and the computing time. Finally, we illustrate our proposal with the analysis of two real datasets: a two dimensional example of historical records of monthly precipitation data in USA and a three dimensional one of mortality data from respiratory disease according to the age at death, the year of death and the month of deathThe authors would like to express their gratitude for the support received in the form of the Spanish Ministry of Economy and Competitiveness grants MTM2011-28285-C02-01 and MTM2011-28285-C02-02. Work of Mar a Xose Rodríguez - Alvarez was supported by grant CA09/0053 from the Instituto de Salud Carlos III. The research of Dae-Jin Lee was funded by an NIH grant for the Superfund Metal Mixtures, Biomarkers and Neurodevelopment project 1PA2ES016454-01A

Enterprise Paternalism and "Desarrollismo". Reflections about the Building of the Mining Town of Fontao

Texto dispoñible en galego e españolNeste traballo estúdase a creación dun espazo urbano-industrial na contorna das minas de estaño e de volframio de Fontao (Pontevedra), enmarcándoo no proceso de modernización da empresa mineira. A política de xestión da man de obra recolle, en parte, os presupostos do chamado “paternalismo industrial”En este trabajo se estudia la creación de un espacio urbano-industrial en el entorno de las minas de estaño y volframio de Fontao (Pontevedra), enmarcándolo en el proceso de modernización de la empresa minera. La política de gestión de la mano de obra recoge, en parte, los presupuestos del llamado “paternalismo industrial"It focus on the creation of an urban-industrial space in the surroundings of the tin and wolfram mines of Fontao (Pontevedra), fixing it into the modernization process of the mining enterprise. The labour force management policy pick up, partly, the budgets of the so-called “enterprise paternalismS

Migratory Networks vs. Economic Networks. Social and Labour Insertion and Contribution of the Galician People to Development of México

Texto dispoñible en galego e españolO interese do estudo da emigración galega en México, desde a perspectiva do papel das redes e das cadeas migratorias, radica en varias consideracións. A primeira é a súa mesma contemporaneidade Trátase, ademais, dunha emigración relativamente minoritaria, pero cualitativamente moi importante, que alcanzou un éxito económico notable e que se afianzou desde a década dos anos cincuenta como o primeiro colectivo, pola súa importancia económica e numérica, no conxunto da colonia española daquel país. O feito de constituír un movemento migratorio cunha xeografía de procedencia concentrada permite unha forte redución nos custos de información á hora de elixir o destino migratorio. Estas redes, baseadas en relacións locais primarias, son as responsables do elevado nivel de eficacia na transmisión da información imprescindible para tomar a decisión de emigrar, obter os medios materiais para a viaxe e, moi especialmente, á hora de integrarse no mercado laboral mexicano. Esta vantaxe comparativa está na base do éxito económico que a emigración galega tivo en México na segunda metade do século XX. As fortes redes económicas e sociais establecidas pola emigración galega en México tiveron unha importante repercusión en Galicia debido ás peculiaridades que reviste o retorno, xa que o regreso, agás moi raras excepcións, nunca supón unha ruptura persoal e de negocios co país de destinoEl interés del estudio de la emigración gallega en México, desde la perspectiva del papel de las redes y de las cadenas migratorias, radica en varias consideraciones. La primera es su misma contemporaneidad. Se trata, además, de una emigración relativamente minoritaria, pero cualitativamente muy importante, que ha alcanzado un éxito económico notable y que se ha afianzado desde la década de los años cincuenta como el primer colectivo, por su importancia económica y numérica, en el conjunto de la colonia española de aquel país. El hecho de constituir un movimiento migratorio con una geografía de procedencia concentrada permite una fuerte reducción en los costes de información a la hora de elegir el destino migratorio. Estas redes, basadas en relaciones locales primarias, son las responsables del elevado nivel de eficacia en la transmisión de la información imprescindible para tomar la decisión de emigrar, obtener los medios materiales para el viaje y, muy especialmente, a la hora de integrarse en el mercado laboral mexicano. Esta ventaja comparativa está en la base del éxito económico que la emigración gallega ha tenido en México en la segunda mitad del siglo XX. Las fuertes redes económicas y sociales establecidas por la emigración gallega en México han tenido una importante repercusión en Galicia debido a las peculiaridades que reviste el retorno, ya que el regreso, salvo muy raras excepciones, nunca supone una ruptura personal y de negocios con el país de destinoThe interest for the study of the Galician emigration to México, from a perspective of the role of the migratory networks and links, lies in different considerations. Firstly because this migratory cycle survives until the 80’s of the XX century. Furthermore it is relatively a minority emigration, but very important qualitatively, having a notable economic success, and from the 50’s of the XX century being the most important Spanish colony in Mexico from the economic and population number point of views. The fact of being a migratory movement with a concentrate point of departure leads to a relatively facility for the diffusion of the information. The existence of these networks, based in primary local relations, is the reason of the high efficiency level in the transmission of the indispensable information for deciding to migrate and to integrate in the Mexican labour market. These strong economic and social networks, established by the Galician emigration in México, have got a important repercussions in Galicia, because of the returning peculiarity that, saving a very strange exceptions, never suppose a personal and business rupture with the destiny countryS

Multidimensional adaptive P-splines with application to neurons' activity studies

The receptive field (RF) of a visual neuron is the region of the space that elicits neuronal responses. It can be mapped using different techniques that allow inferring its spatial and temporal properties. Raw RF maps (RFmaps) are usually noisy, making it difficult to obtain and study important features of the RF. A possible solution is to smooth them using P-splines. Yet, raw RFmaps are characterized by sharp transitions in both space and time. Their analysis thus asks for spatiotemporal adaptive P-spline models, where smoothness can be locally adapted to the data. However, the literature lacks proposals for adaptive P-splines in more than two dimensions. Furthermore, the extra flexibility afforded by adaptive P-spline models is obtained at the cost of a high computational burden, especially in a multidimensional setting. To fill these gaps, this work presents a novel anisotropic locally adaptive P-spline model in two (e.g., space) and three (space and time) dimensions. Estimation is based on the recently proposed SOP (Separation of Overlapping Precision matrices) method, which provides the speed we look for. Besides the spatiotemporal analysis of the neuronal activity data that motivated this work, the practical performance of the proposal is evaluated through simulations, and comparisons with alternative methods are reported.</p

Application of Generalized Additive Models to the Evaluation of Continuous Markers for Classification Purposes

Background: Receiver operating characteristic (ROC) curve and derived measures as the Area Under the Curve (AUC) are often used for evaluating the discriminatory capability of a continuous biomarker in distinguishing between alternative states of health. However, if the marker shows an irregular distribution, with a dominance of diseased subjects in noncontiguous regions, classification using a single cutpoint is not appropriate, and it would lead to erroneous conclusions. This study sought to describe a procedure for improving the discriminatory capacity of a continuous biomarker, by using generalized additive models (GAMs) for binary data.Methods: A new classification rule is obtained by using logistic GAM regression models to transform the original biomarker, with the predicted probabilities being the new transformed continuous biomarker. We propose using this transformed biomarker to establish optimal cut-offs or intervals on which to base the classification. This methodology is applied to different controlled scenarios, and to real data from a prospective study of patients undergoing surgery at a University Teaching Hospital, for examining plasma glucose as postoperative infection biomarker.Results: Both, theoretical scenarios and real data results show that when the risk marker-disease relationship is not monotone, using the new transformed biomarker entails an improvement in discriminatory capacity. Moreover, in these situations, an optimal interval seems more reasonable than a single cutpoint to define lower and higher disease-risk categories.Conclusions: Using statistical tools which allow for greater flexibility (e.g., GAMs) can optimize the classificatory capacity of a potential marker using ROC analysis. So, it is important to question linearity in marker-outcome relationships, in order to avoid erroneous conclusions

Multidimensional Adaptive Penalised Splines with Application to Neurons' Activity Studies

P-spline models have achieved great popularity both in statistical and in applied research. A possible drawback of P-spline is that they assume a smooth transition of the covariate effect across its whole domain. In some practical applications, however, it is desirable and needed to adapt smoothness locally to the data, and adaptive P-splines have been suggested. Yet, the extra flexibility afforded by adaptive P-spline models is obtained at the cost of a high computational burden, especially in a multidimensional setting. Furthermore, to the best of our knowledge, the literature lacks proposals for adaptive P-splines in more than two dimensions. Motivated by the need for analysing data derived from experiments conducted to study neurons' activity in the visual cortex, this work presents a novel locally adaptive anisotropic P-spline model in two (e.g., space) and three (space and time) dimensions. Estimation is based on the recently proposed SOP (Separation of Overlapping Precision matrices) method, which provides the speed we look for. The practical performance of the proposal is evaluated through simulations, and comparisons with alternative methods are reported. In addition to the spatio-temporal analysis of the data that motivated this work, we also discuss an application in two dimensions on the absenteeism of workers

On the estimation of variance parameters in non-standard generalised linear mixed models: application to penalised smoothing

We present a novel method for the estimation of variance parameters in generalised linear mixed models. The method has its roots in Harville (J Am Stat Assoc 72(358):320-338, 1977)'s work, but it is able to deal with models that have a precision matrix for the random effect vector that is linear in the inverse of the variance parameters (i.e., the precision parameters). We call the method SOP (separation of overlapping precision matrices). SOP is based on applying the method of successive approximations to easy-to-compute estimate updates of the variance parameters. These estimate updates have an appealing form: they are the ratio of a (weighted) sum of squares to a quantity related to effective degrees of freedom. We provide the sufficient and necessary conditions for these estimates to be strictly positive. An important application field of SOP is penalised regression estimation of models where multiple quadratic penalties act on the same regression coefficients. We discuss in detail two of those models: penalised splines for locally adaptive smoothness and for hierarchical curve data. Several data examples in these settings are presented.This research was supported by the Basque Government through the BERC 2018-2021 program and by Spanish Ministry of Economy and Competitiveness MINECO through BCAM Severo Ochoa excellence accreditation SEV-2013-0323 and through projects MTM2017-82379-R funded by (AEI/FEDER, UE) and acronym “AFTERAM”, MTM2014-52184-P and MTM2014-55966-P. The MRI/DTI data were collected at Johns Hopkins University and the Kennedy-Krieger Institute. We are grateful to Pedro Caro and Iain Currie for useful discussions, to Martin Boer and Cajo ter Braak for the detailed reading of the paper and their many suggestions, and to Bas Engel for sharing with us his knowledge. We are also grateful to the two peer referees for their constructive comments of the paper

On the optimism correction of the area under the receiver operating characteristic curve in logistic prediction models

When the same data are used to fit a model and estimate its predictive performance, this estimate may be optimistic, and its correction is required. The aim of this work is to compare the behaviour of different methods proposed in the literature when correcting for the optimism of the estimated area under the receiver operating characteristic curve in logistic regression models. A simulation study (where the theoretical model is known) is conducted considering different number of covariates, sample size, prevalence and correlation among covariates. The results suggest the use of k-fold cross-validation with replication and bootstrap

Analysing visual receptive fields through generalised additive models with interactions

Visual receptive fields (RFs) are small areas of the visual field where a stimulus induces a responses of a particular neuron from the visual system. RFs can be mapped using reverse crosscorrelation technique, which produces raw matrices containing both spatial and temporal information about the RF. Though this technique is frequently used in electrophysiological experiments, it does not allow formal comparisons between RFs obtained under different experimental conditions. In this paper we propose the use of Generalised Additive Models (GAM) including complex interactions, to obtain smoothed spatio-temporal versions of RFs. Moreover, the proposed methodology also allow for the statistical comparisons of the RFs obtained across various experimental conditions. Data analysed here derive from studies of neurons' activity in the visual cortex of behaving monkeys. Our results suggest that the GAM-based technique proposed in this paper can be a flexible and powerful tool for assessing receptive field properties