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Personal information:

Name: Carmen Cadarso Suárez

Position: Full Professor of Biostatistics

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Biographical background:

Carmen Cadarso Suárez, director of the Interdisciplinary Centre of Biostatistics at the University of Santiago de Compostela (ICBUSC) and professor at the Department of Statistics of the University of Santiago de Compostela (USC).

She has a history of over 30 years both as a teacher and a coordinator of projects and research networks. She is specialized in nonparametric inference curves and bootstrap inference techniques, with special emphasis on survival analysis with censored data and GAM models, all applied in various areas of biomedicine. The research work generated more than hundred publications in international journals of impact in different areas of knowledge; in Statistics (JASA, Stat Med, Biostatistics, Statistical methods in medical research, Test, Lifetime Data Anal, Biometrical Journal, ...), Computer Science (Statistics and Computing, CSDA, ...) and Biomedicine, amongst others.

She currently directs the Interdisciplinary Group of Statistics, Computing, Medicine and Biology (GRIDECMB), with is affiliated with the Health Research Institute of Santiago (IDIS), referenced by the Instituto de Salud Carlos III as an institute of scientific excellence. Based on her methodological and applicational contributions in biomedicine, she was selected as a member of CIMUS, a unique biomedical research center of the USC.

She is the main promoter of the academic spin-off BIOSTATECH, chairing its Scientific Committee which determines the methodological and statistical basis on which the work is been developed by the company.

She also directs the National Network of Biostatistics (BIOSTATNET). This network, a pioneer in Spain, is interdisciplinary with statistical members, mathematicians, biologists, physicians, and computer scientists from various Spanish universities and biomedical institutions, and has a representation of prestigious European biostatisticians, Latin America and the United States; funded by the Ministry of Economy and Finance.



Faculty of Medicine (USC)
+34 881 812 282 12282



Selected publications:

  • Roca-Pardiñas J, Cadarso-Suárez C, González-Manteiga W (2005). Testing for interactions in Generalized Additive Models: Application to SO2 Pollution Data. Statistics and Computing; 15: 289-299.
  • Cadarso-Suárez C, Roca-Pardiñas J, Figueiras A (2006). Effect measures in nonparametric regression with interactions between continuous exposures. Statistics in Medicine; 25: 603-621.
  • Faes C, Heys H, Molenberghs G, Aerts M, Cadarso-Suárez C, Acuña C, Cano M (2008). A Flexible Method to Measure Synchrony in Neuronal Firing. Journal of the American Statistical Association; 103: 149-161.
  • Machado L, Cadarso-Suárez C, de Uña-Álvarez J, Andersen PK (2009). Multi-state models for the analysis of time to event data. Statistical Methods in Medical Research; 18 (2): 195-222.
  • Cid-Álvarez B, Gude F, Cadarso-Suárez CM, Rodríguez-Álvarez MX, González-Babarro E, García-Acuña JM, González-Juanatey JR (2009). Admission and fasting plasma glucose for estimating  risk of death of diabetic and non-diabetic patients with acute coronary syndrome: nonlinearity of hazard ratios, and time-dependent comparison. Am Heart J; 158(6): 989-97.
  • Maringwa JT, Faes C, Geys H, Molenberghs G, Cadarso-Suárez C, Pardo-Vázquez JL, Leborán V, Acuña C. Application of Penalized Smoothing Splines in Analyzing Neuronal Data. Biometrical Journal; 51(1): 203-216.
  • Rodríguez-Álvarez MX, Roca Pardiñas J, Cadarso-Suárez CM (2011). ROC curve and covariates: extending the induced methodology to the non-parametric framework. Statistics and Computing; 21: 483-499.
  • Roca-Pardiñas J, Cadarso-Suárez C, Pardo-Vázquez J.L,  Leborán V, Molenberghs G, Faes C, Acuña C (2011). Assessing neural activity related to decision-making through flexible odds ratio curves and their derivatives. Statistics in Medicine; 30(14):1695-1711.
  • Inácio V, González-Manteiga, W; Febrero-Bande, M; F Gude; Alonzo, T.A., and Cadarso Suárez, C (2012). Extending induced ROC methodology to the functional context. Biostatistics; 13 (4): 594-608.
  • Rodríguez Girondo M, Kneib T., Cadarso-Suárez C. and Abu-Assi E (2013). Model Building in Non Proportional Hazard Regression.  Statistics in Medicine; 32(30): 5301-5314.
  • López-Ratón M, Rodríguez-Álvarez MX, Cadarso-Suárez C, Gude  F (2014). OptimalCutpoints: An R package for selecting optimal cutpoints in diagnostic tests. Journal of Statistical Software; 61(8): 1-36.
  • Duarte E, de Sousa B, Cadarso-Suarez C, Rodrigues V, Kneib T. (2014). Structured additive regression modeling of age of menarche and menopause in a breast cancer screening program. Biometrical Journal; 56(3): 416-427.

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