Galicia node consists of 41 members leaded by Carmen Cadarso Javier Roca, José A. Vilar and Francisco Gude doing research in areas such as Generalized Additive Models (GAM) Inference, Extensions to the GAM model, Multi-state Additive models (MSM) in survival analysis
1. National Project
Project Title: GENERALIZED ADDITIVE MODELS for ASSOCIATION, PREDICTION and CLASSIFICATION studies. APPLICATIONS to MEDICINE and BIOLOGY.
Project Code: MTM2008-01603.
Main Researcher: Carmen María Cadarso Suárez.
2. Researchers that constitute the node
33 researchers from both university and health areas constitute the node. Most of them are active members of the national project MTM2008-01603 that also counts with the participation of researchers from projects MTM2008-03129, MTM2008-00166 and MTM2008-03010. It is a multidiciplinary team including biostatisticians, doctors, biologists, physicists, economists and an IT technician.
Leading Researcher (IR)
Carmen María Cadarso Suárez
Researchers from National Universities
Xosé Luis Otero Cepeda
Pablo García Tahoces
Mónica López Ratón
Isabel Martínez Silva
Anaderli Torres Ortiz
Vicente Lustres Pérez
Javier Roca Pardiñas (responsible for node´s Universidad de Vigo section)
Jacobo de Uña Álvarez
Mar Rodríguez Girondo
José Antonio Vilar Fernández (responsible for node´s Universidade da Coruña section)
María Amalia Jácome Pumar
María Graciela Estévez Pérez
María Ausencia Tome Martínez de Rituerto
Rosa Crujeiras Casais
María del Carmen Carollo Limeres
María José Lombardía Cortiña
Researchers from International Universities
Luis Meira Machado
Bruno de Sousa
Inês Pereira Silva Cunha Sousa
Carlos Daniel Paulino
Giovani Loiola da Silva
Researchers from Biomedical Institutions
Francisco Gude Sampedro (responsible for node´s CHUS section)
Pilar Gayoso Diz
María Xosé Rodríguez Álvarez
Arturo González Quintela
Francisco Reyes Santías
Sonia Pértega Díaz
María Teresa Seoane Pillado
Xurxo Hervada Vidal
María Isolina Santiago Pérez
Miguel Ángel Rodríguez Muíños
Alberto Malvar Pintos
Salvador Pita Fernández
María Pazos Pata
3. Main lines of research
Generalized Additive Models (GAM) represent a flexible tool in multivariate regression studies. In this kind of models the researcher does not need to assume parametric form for the effects of the covariates in the response. Its versatility allows for several extensions: a) GAM with interactions and unknown link function b) Multistate survival models c) Multivariate Response Models (VGAM). d) Conditioned ROC curves (on covariates). Amongst these models´ immediate application areas it is worth mention Medicine (Clinical, Epidemiology, Neuroscience and Forensic Medicine and also Biology. In particular, they are essential for Clinical diagnosis and are becoming more and more useful in Epidemiology.
Amongst this node´s main lines of research
Apart from the methodological objectives mentioned above and due to the fact that many of the statistical projects developed have appeared as methodological challenges born from biomedical research projects, it is believed that there is a need to transfer this knowledge to society and those areas of application of biostatistics. This leads to the main objectives:
(a) Application of the proposed methodology to real data from Medicine and Biostatistics areas:
(a1) Measures of association in Clinical Medicine and Epidemiology: non parametric estimation of continuous varuablese effect measurement curves like Odds-Ratio (OR), Relative Risk (RR) and Hazard Ratio (HR).
(a2) Neuronal firing rate. Measurement of neuronal time sinchrony. Neuronal population analysis.
(a3) Prediction of Post-Mortem interval in Forensic Medicine through GAM models, SVM (Support Vector Machines) and Neural Networks.
(a4) ROC regression analysis in clinical diagnosis. Statistical evaluation of CAD systems (Computer-Aided Diagnosis) for breast cancer.
(a5) Growth curves in Medicine and Marine Biology. Smooth quantile regression.
(a6) Marine invertebrates reproductive cycle modelling (GAM) applied to marine resources management.
(a7) Modelling of complex survival processes in HIV/AIDS and cancer through flexible MSMs.
(a8) Diseasse mapping.
(a9) Modelling of spatial patterns in biodiversity.
(b) Development of friendly software for those professionals in the medical and biological sciences interested in the practical application of the proposed statistical methodology.
4. Institutions and groups with whom the node collaborates
5. Biostatistics Consulting Services
Biostatistics consulting services are developed in several centres (Spanish Institutions involved in Galicia Node as shown in chart) :
The CHUS Support Unit for Research provides methodological support to the centre´s different hospitals.
The Coruña University Hospital Complex (CHUAC) Support Unit provides methodological support to the centre´s different hospitals.
USC Medical School Biostatistics Unit integrates research in biostatistics with education and knowledge transfer through cooperation in the execution of the resulting documents and collaboration in research projects in Biomedicine and Statistics (see I.P.´s curriculum vitae).
The Centre for Research Molecular Medicine and Chronical Diseases (CIMUS) where the IP and her team will be moving soon in will be also carrying out transfer activities in order to execute biostatistical research tasks in the biomedical area. This action will further extend to collaborations with members from the Santiago´s Sanitary Research Institute (IDIS).